{"as_of":"2026-08-10T23:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec76edfcfe521f909b7020ee757a111a693a188b7cea202f541528eb3215d6ca","coverage":[{"denominator":125,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T22:30:41.854233Z","state":"measured"},{"denominator":101,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":101,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-18T10:45:18.830629Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-18T10:46:16.182778Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"cited_work":{"arxiv_id":"2501.18804","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2501.18804","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Work in progress","venue":null,"work_id":"22102e90-a4d0-47ac-bff7-560147906ce9","year":null},"citing_paper":{"arxiv_id":"2510.00978","last_updated":"2026-04-07T12:15:00Z","snapshot_observed_at":"2026-08-08T14:03:30.879010Z","submitted_at":"2025-10-01T14:52:12Z","title":"A Scene is Worth a Thousand Features: Feed-Forward Camera Localization from a Collection of Image Features","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-18T10:45:18.830629Z"},"links":{"cited_paper":"/paper/2501.18804","citing_paper":"/paper/2510.00978"},"observation_digest":"sha256:e4c79e52fe6f99fc3347610699f85810742181415fc020b69d0a4e1cc5f7733a","observation_id":"dfec715d-cd37-4cd0-a9ff-93ddd733c5e6","resolution":{"observed_at":"2026-05-18T10:46:16.186893Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.18804/citation-record","integrity":"/paper/2501.18804/integrity","json":"/paper/2501.18804/citation-record.json","paper":"/paper/2501.18804"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.491843Z","title":"https://github.com/webdataset/ webdataset, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.491843Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:4dd8883f5d06a42c73825437c7e81ee99b50bc2b4aed97ff8387264d042234a7","observation_id":"9581ccb1-74e9-455f-8039-aec64d495858","resolution":{"observed_at":"2026-08-09T22:30:41.491843Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.495346Z","title":"STORM: Spatio-temporal reconstruction model for large-scale outdoor scenes","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.495346Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:5ef8887b837fa971888c3e69bdd7ef96ea9b03c6a6f61b3a8506ea40a707eed5","observation_id":"dd995b57-16cf-4c72-a320-b570a83e5f16","resolution":{"observed_at":"2026-08-09T22:30:41.495346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.499645Z","title":"Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.499645Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:7b7735ebd8b9a75cae934859af1923af79b859457007cda1b4b03cb9e62ef5d2","observation_id":"3747ebbe-3d36-485a-bc91-27a96da49f88","resolution":{"observed_at":"2026-08-09T22:30:41.499645Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.504425Z","title":"Barron, Ben Mildenhall, Dor Verbin, Pratul P","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.504425Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e8cca3ff3f6c997bb33f334644cd9ada4e7ebbfda59fd2ec799f67e02111c0a6","observation_id":"4fba1c23-8202-480a-9410-50506c7a599b","resolution":{"observed_at":"2026-08-09T22:30:41.504425Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.508551Z","title":"Zoedepth: Zero-shot trans- fer by combining relative and metric depth, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.508551Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:a0bb00ee02f0524aa2e789d825dc6b6d1ff6603db1a8b5912b82307edf403a3c","observation_id":"fbee8ef7-0481-4270-9c7e-1545c57c97cb","resolution":{"observed_at":"2026-08-09T22:30:41.508551Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.511788Z","title":"Midas v3.1 – a model zoo for robust monocular relative depth estima- tion, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.511788Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:7063bc16b7080d93ca8fc57e765b443e6741b0bfa7d57f107f855e32bf1b9df0","observation_id":"196ca915-5361-47df-b20e-f40f1fde7c56","resolution":{"observed_at":"2026-08-09T22:30:41.511788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.10773","last_updated":"2020-01-29T12:13:20Z","snapshot_observed_at":"2026-07-06T08:53:28.193420Z","submitted_at":"2020-01-29T12:13:20Z","title":"Virtual KITTI 2","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.10773","snapshot_observed_at":"2026-08-09T22:30:41.515314Z","title":"Virtual kitti 2","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.515314Z"},"links":{"cited_paper":"/paper/2001.10773","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:89caa41b1fbb814535dfd9fbaf4a07bb33e653aeff3b21c3e44028a588a8bd2a","observation_id":"657b3c49-5f4d-453b-b793-22776a051ec3","resolution":{"observed_at":"2026-08-09T22:30:41.515314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.519187Z","title":"nuscenes: A mul- timodal dataset for autonomous driving","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.519187Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:80aa2c9645387cd6624f95b1c8d9d1042b47313a2bf5d540f430c0015a3e093d","observation_id":"dead24b1-e6a0-47c9-a75a-ec3cb9074bce","resolution":{"observed_at":"2026-08-09T22:30:41.519187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.14756","last_updated":"2024-02-06T02:57:35Z","snapshot_observed_at":"2026-08-04T16:41:46.813009Z","submitted_at":"2022-05-29T20:07:23Z","title":"EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.14756","snapshot_observed_at":"2026-08-09T22:30:41.522452Z","title":"Effi- cientvit: Enhanced linear attention for high-resolution low-computation visual recognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.522452Z"},"links":{"cited_paper":"/paper/2205.14756","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:8d0f5bbfb32c946ae77ec6b11c044c2d4a45aac658d78db9c0a17370acb69036","observation_id":"867d327a-e4e6-4249-b4bb-5aa64d5fb3c2","resolution":{"observed_at":"2026-08-09T22:30:41.522452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.525835Z","title":"pi-gan: Periodic implicit genera- tive adversarial networks for 3d-aware image synthesis","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.525835Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:4651e388c456588059d7bcf13725f772c69168573dd1edf8b1c9c277a64513ae","observation_id":"31d32300-e1c0-4e1e-90ae-936438cf94f7","resolution":{"observed_at":"2026-08-09T22:30:41.525835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.529197Z","title":"Chan, Connor Z","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.529197Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:9273b3ed4b5f9ab6932ba920786d0664bf73800b2d9e8dbe66275de8611df0c3","observation_id":"81d1c2d6-12e1-400c-9b0f-f5e73652b5b2","resolution":{"observed_at":"2026-08-09T22:30:41.529197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.532594Z","title":"Chan, Koki Nagano, Matthew A","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.532594Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:b069c32e4ebcece1aa6bc4a62f6147ee664df7c01afa9e1fb48281cdb46c1de3","observation_id":"1c8273ba-de28-4db3-a5d0-18a8e998edcd","resolution":{"observed_at":"2026-08-09T22:30:41.532594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.535807Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.535807Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:db84dfb592b44190519a1c4718d21b0c32793159ba473d75ed87c58596a4bd12","observation_id":"cc17270c-f4f6-416e-9213-e42d63193f8a","resolution":{"observed_at":"2026-08-09T22:30:41.535807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.540111Z","title":"pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.540111Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e3114d8f05839df530b608bf84c175b16b099afbb06c471809ad98ec52c76e70","observation_id":"798d809c-b468-4d54-8c18-f538b102693c","resolution":{"observed_at":"2026-08-09T22:30:41.540111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.14627","last_updated":"2024-07-18T13:10:22Z","snapshot_observed_at":"2026-08-10T15:32:19.675052Z","submitted_at":"2024-03-21T17:59:58Z","title":"MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.14627","snapshot_observed_at":"2026-08-09T22:30:41.543700Z","title":"Mvsplat: Efficient 3d gaussian splat- ting from sparse multi-view images","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.543700Z"},"links":{"cited_paper":"/paper/2403.14627","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:5879073e498d0a2108cbeb604b8ef7e32b5545eac16930b660e3c48fffe08797","observation_id":"cfa67c2a-5fe0-4d38-8c6d-2611095be5a0","resolution":{"observed_at":"2026-08-09T22:30:41.543700Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.547467Z","title":"Chang, Manolis Savva, Maciej Hal- ber, Thomas Funkhouser, and Matthias Nießner","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.547467Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:fb8e8c26e66277d3225402f328c040e45289fe3b6fd8dc5f84c7339a1f723d90","observation_id":"3e8117d0-5db8-470d-9843-d52314958dc5","resolution":{"observed_at":"2026-08-09T22:30:41.547467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.02791","last_updated":"2024-10-17T16:11:28Z","snapshot_observed_at":"2026-08-09T17:15:20.152760Z","submitted_at":"2021-07-06T17:58:35Z","title":"Depth-supervised NeRF: Fewer Views and Faster Training for Free","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.02791","snapshot_observed_at":"2026-08-09T22:30:41.551182Z","title":"Depth-supervised nerf: Fewer views and faster training for free","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.551182Z"},"links":{"cited_paper":"/paper/2107.02791","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:efbeca5f8c08393d532f3ab3f09e63cf127746d44d54f887e26497ac2d89e997","observation_id":"67ee91e1-0d0a-446b-b0e5-0b634780098e","resolution":{"observed_at":"2026-08-09T22:30:41.551182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.554956Z","title":"Uncon- strained scene generation with locally conditioned radiance fields","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.554956Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:5ae030ba9093cad755b9d76cf9cf3641435b2bfc2458ec07ab6bef809e6e7b6f","observation_id":"f7a1e857-4d55-41a8-be1e-20860df41a7e","resolution":{"observed_at":"2026-08-09T22:30:41.554956Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.559103Z","title":"Diffusion models beat gans on image synthesis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.559103Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:89d7ffe01db3133200fb76ca82951d5eb3fc8552004dc9546ba49811178a7be3","observation_id":"18aca851-8d6b-4233-ab37-820a74837688","resolution":{"observed_at":"2026-08-09T22:30:41.559103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.562511Z","title":"Learning to render novel views from wide-baseline stereo pairs","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.562511Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3990d46cdf3236b1822e536572a863daad5016305f58e60498bcda92ebdd7d4c","observation_id":"35d7bf19-b248-4650-a3b2-0a18cb91f33a","resolution":{"observed_at":"2026-08-09T22:30:41.562511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.566948Z","title":"Omnidata: A scalable pipeline for making multi- task mid-level vision datasets from 3d scans","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.566948Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:998066386e97e8ca3531c8e850bb7dfbbd29f2a74eb3f1ab7ce1a2416bd4b37b","observation_id":"1427b4ac-c1b2-425f-85e7-0602400fd757","resolution":{"observed_at":"2026-08-09T22:30:41.566948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.570095Z","title":"Self-supervised camera self-calibration from video","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.570095Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:5f7536dc96e3ee08a85bb02d9a4f8f4def75c1c2c55e6a3a9bae0adea83fb4d5","observation_id":"04b78d91-a00b-4da2-a19c-301b52f5d4fa","resolution":{"observed_at":"2026-08-09T22:30:41.570095Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.573690Z","title":"Ge- owizard: Unleashing the diffusion priors for 3d geometry estimation from a single image","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.573690Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:ed0b3cb0e4e8d3be4cda179570848ff788a12445f77321717e59d1bbbef2f247","observation_id":"0e4bea80-14b0-4043-8eb4-e4701b14ca0d","resolution":{"observed_at":"2026-08-09T22:30:41.573690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.577206Z","title":"Srini- vasan, Jonathan T","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.577206Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:dfd29cdf46694cace1674d3a8314400ad08defe18165286aab2bb1d018c7f9b1","observation_id":"3e1d3b89-0266-4a75-b1df-f3194b84a5a9","resolution":{"observed_at":"2026-08-09T22:30:41.577206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.582036Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.582036Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:b28205c3a5c4ba3333fcbca6b4a8bd2129e5b79c27a518261d30c40d4bd58052","observation_id":"e730ad1c-02e1-426f-99a6-cfe690a3af82","resolution":{"observed_at":"2026-08-09T22:30:41.582036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.585253Z","title":"Accurate, large minibatch sgd: Training imagenet in 1 hour, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.585253Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:939edb6d226413991b748d20d3192176742ed1a6b10858003655d141b6934477","observation_id":"80d5fe19-0a32-4e1f-978e-934b47750ec3","resolution":{"observed_at":"2026-08-09T22:30:41.585253Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.588676Z","title":"16 Nerfdiff: Single-image view synthesis with nerf-guided dis- tillation from 3d-aware diffusion","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.588676Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:a61a6ee464241c12f395b9643f6870be9ba395f61d01ac32f5adbb8fbf65ed21","observation_id":"25c3da41-1203-46aa-a592-847500ac953b","resolution":{"observed_at":"2026-08-09T22:30:41.588676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.592069Z","title":"Sparsenerf: Distilling depth ranking for few-shot novel view synthesis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.592069Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:329b396ef98cb5b3e0d52881684d330a24d1664689744f14f3a0205425de0746","observation_id":"56e00c32-3351-4d17-9ea8-6a25c0ecdfd6","resolution":{"observed_at":"2026-08-09T22:30:41.592069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.595692Z","title":"Depthfm: Fast monocular depth estimation with flow matching, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.595692Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:bc594eb2aab27e3f4af13d523ea57fec72cf32e50121584dd2664480340e812f","observation_id":"7444edc4-6f24-41fb-b0d0-2bda896cdfc6","resolution":{"observed_at":"2026-08-09T22:30:41.595692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.598663Z","title":"3d packing for self-supervised monocular depth estimation","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.598663Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:c36a92f12366aeb81bb939d5a6ec5612f228f1974a9da2de918aeb7cdc726bd5","observation_id":"b78f95c2-61a4-46bc-9f53-17d0e7f461c1","resolution":{"observed_at":"2026-08-09T22:30:41.598663Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.602181Z","title":"Semantically-guided representation learning for self-supervised monocular depth","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.602181Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:c346421776eef8ab5b2a215eabb6aed9a3654218aac57a7ac44a4c99b37a3357","observation_id":"4fc98ec3-2da4-4373-a6a9-bb4eb779ba09","resolution":{"observed_at":"2026-08-09T22:30:41.602181Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.605642Z","title":"Geometric unsupervised domain adaptation for semantic segmentation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.605642Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:2280a8730185a8472194dd074c60476e975d30c9b91003e181d8ad893eedd8f8","observation_id":"70b67582-f515-4962-9516-427fedcd3d8b","resolution":{"observed_at":"2026-08-09T22:30:41.605642Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.00152","last_updated":"2021-03-31T22:52:04Z","snapshot_observed_at":"2026-08-07T00:27:02.709401Z","submitted_at":"2021-03-31T22:52:04Z","title":"Full Surround Monodepth from Multiple Cameras","version":1},"cited_work":{"arxiv_id":"2104.00152","doi":null,"metadata_source":"pith","pith_arxiv_id":"2104.00152","snapshot_observed_at":"2026-08-09T22:30:42.140323Z","title":"Full Surround Monodepth from Multiple Cameras","venue":"cs.CV","work_id":"24439e00-c497-4d48-a0f7-4e5a4908811c","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.609338Z"},"links":{"cited_paper":"/paper/2104.00152","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:56b4da301e6e531e317b42dc6424cda20d6a7288f855bb934c4bb235fbcafbe4","observation_id":"c0816e8c-5650-48d4-9c91-0d7b2c529501","resolution":{"observed_at":"2026-08-09T22:30:42.223165Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.613369Z","title":"Multi-frame self-supervised depth with transformers","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.613369Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:5e3a69beaeb0a520df8152ebd79ab9ebf02d6afff03b60470596b66d3a3b22ae","observation_id":"f77d83d4-589d-42e9-94e9-71f2bd575561","resolution":{"observed_at":"2026-08-09T22:30:41.613369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.617119Z","title":"Learning optical flow, depth, and scene flow with- out real-world labels","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.617119Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:c3c3a946ef602226b1526af485ac98e94896d6740ca50d779c2c98ab076da692","observation_id":"1302ab7b-a6b9-4336-af1f-9692c3417a46","resolution":{"observed_at":"2026-08-09T22:30:41.617119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.620940Z","title":"Depth field networks for generalizable multi-view scene representation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.620940Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:eeb6e6b2b9b3fb8375d93cc65c3e299e451468f1b2037a9a72736549826717db","observation_id":"26142837-1736-430f-b35b-f347595b0796","resolution":{"observed_at":"2026-08-09T22:30:41.620940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.624497Z","title":"Towards zero-shot scale-aware monoc- ular depth estimation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.624497Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:adb114772c00390833148056856ae2e456c35436f15305487614958b2f680997","observation_id":"21e29fe1-9336-4c92-8f2d-2b9bcda28be0","resolution":{"observed_at":"2026-08-09T22:30:41.624497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.627788Z","title":"Delira: Self-supervised depth, light, and radiance fields","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.627788Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:25b707fe924458eeae9899b91e3ce784bb32f04a10c400e42245ef51061f8123","observation_id":"748a4516-4013-4695-910d-c6ab46035ca5","resolution":{"observed_at":"2026-08-09T22:30:41.627788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.631033Z","title":"Grin: Zero-shot metric depth with pixel-level dif- fusion, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.631033Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:757b8083fafbc95099ee220ea3fa004bd0ba8f34e4626f38cdeac9626e4f3c69","observation_id":"bb2e2a45-f31b-4ef6-aaec-b1d7c5d24702","resolution":{"observed_at":"2026-08-09T22:30:41.631033Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.634565Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.634565Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:d3e07d9ae2e6936288485e8105da086076908f4af3db75dd1a1108da35d751f1","observation_id":"e6301d55-3f49-4399-9024-c9ce92ae8663","resolution":{"observed_at":"2026-08-09T22:30:41.634565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.638189Z","title":"Cascaded diffusion models for high fidelity image generation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.638189Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:829c7248c4a802cc2920c1b673b956d4bbc722458b89220286b79569f39e8732","observation_id":"c32612d0-b60d-41d8-a55a-f6820e01b46e","resolution":{"observed_at":"2026-08-09T22:30:41.638189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.641597Z","title":"One thousand and one hours: Self-driving motion prediction dataset","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.641597Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3aeb0783d4d9666e455b2ccd08432d6d6632873c4276d54784379815c9ad8593","observation_id":"a0b453b6-0311-4e7b-9828-d171b0e3c1f8","resolution":{"observed_at":"2026-08-09T22:30:41.641597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.645356Z","title":"Mvd-fusion: Single-view 3d via depth-consistent multi-view generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.645356Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e141edc0f421f3f9c8782e2b6b33aeb16e787aaaa27cbcab9c822f5c0779a902","observation_id":"935b79d3-37b1-4c56-b086-84beb2c793c4","resolution":{"observed_at":"2026-08-09T22:30:41.645356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.15506","last_updated":"2025-01-03T15:39:16Z","snapshot_observed_at":"2026-07-06T18:04:42.102581Z","submitted_at":"2024-03-22T02:30:46Z","title":"Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.15506","snapshot_observed_at":"2026-08-09T22:30:41.649111Z","title":"Metric3d v2: A versatile monocular geomet- ric foundation model for zero-shot metric depth and surface normal estimation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.649111Z"},"links":{"cited_paper":"/paper/2404.15506","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e5fd34b713c2117fdc73e79490e98d3eee9d4f2039566056eee3689c8521523b","observation_id":"0ac27569-e789-4a0e-864c-6a8a9555615a","resolution":{"observed_at":"2026-08-09T22:30:41.649111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02095","last_updated":"2024-11-27T07:59:25Z","snapshot_observed_at":"2026-08-10T14:47:55.222701Z","submitted_at":"2024-09-03T17:52:03Z","title":"DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02095","snapshot_observed_at":"2026-08-09T22:30:41.652803Z","title":"Depthcrafter: Generating consistent long depth sequences for open-world videos","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.652803Z"},"links":{"cited_paper":"/paper/2409.02095","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:29ab280d633f21014054239c96a6c6ef371233c0973b085890775f3bfd1cdc30","observation_id":"7a3929cf-42f4-4668-829a-b3aad5c14d2d","resolution":{"observed_at":"2026-08-09T22:30:41.652803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.00538","last_updated":"2019-05-02T00:59:31Z","snapshot_observed_at":"2026-07-06T07:49:52.652287Z","submitted_at":"2019-05-02T00:59:31Z","title":"DPSNet: End-to-end Deep Plane Sweep Stereo","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.00538","snapshot_observed_at":"2026-08-09T22:30:41.657140Z","title":"Dpsnet: End-to-end deep plane sweep stereo","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.657140Z"},"links":{"cited_paper":"/paper/1905.00538","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:2f7d67a17c91edf45fac15501c2fdc33faa10c89c75081c0a832028e869d883a","observation_id":"75459c8d-12a7-4258-8721-189b5795124d","resolution":{"observed_at":"2026-08-09T22:30:41.657140Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.661212Z","title":"Neo 360: Neural fields for sparse view synthesis of outdoor scenes","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.661212Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3a099ce8e1070d11acf0dbbf50162054ee52e193721df09d0b5b6d3b1d678199","observation_id":"226c4272-e513-4ae9-a937-c56daa2996b9","resolution":{"observed_at":"2026-08-09T22:30:41.661212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.665695Z","title":"Nerf-mae: Masked autoencoders for self-supervised 3d rep- resentation learning for neural radiance fields","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.665695Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e211bbf9401531fcba5498dfbf00b27704e06cc0ca2f9e1fcdeeadb447f2941c","observation_id":"b1b2da4c-6b14-43a3-bf57-8f192eb2f2cf","resolution":{"observed_at":"2026-08-09T22:30:41.665695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.669678Z","title":"Fleet, and Ting Chen","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.669678Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:a304d68a4f3c49987507a5156bb1a186bc232d7ee08be653ede904ce7825b823","observation_id":"2b681d68-7271-48a9-81cd-fedf33d751a6","resolution":{"observed_at":"2026-08-09T22:30:41.669678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.673153Z","title":"Putting nerf on a diet: Semantically consistent few-shot view synthesis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.673153Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:19e08d5db1a25bd619144814ec1aed49d29efbd40943ca62c150fe3acd7e68db","observation_id":"425b5f94-3dfc-435c-8ba5-7946c23c71fa","resolution":{"observed_at":"2026-08-09T22:30:41.673153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.676958Z","title":"Large scale multi-view stereopsis eval- uation","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.676958Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3802e8034ab1e542ecd1bf77e6eaf6043c3f3b207f42cccf47ff9e2e9d10c714","observation_id":"324b8939-e699-439e-a212-676416447eed","resolution":{"observed_at":"2026-08-09T22:30:41.676958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.680759Z","title":"Holodiffusion: Training a 3D diffusion model using 2D images","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.680759Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:f9030667a13386f2e2a29f1361f20f022ec10601f6fdf603830e166c5ad9ecba","observation_id":"87a750a3-7691-4fe6-8734-8add83d96ffa","resolution":{"observed_at":"2026-08-09T22:30:41.680759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.684127Z","title":"Re- purposing diffusion-based image generators for monocular depth estimation, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.684127Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:a59d88bf2e10fd8c1c32646e07bc4e37657ab167de9655039b77fc07bcca9dcb","observation_id":"b2c9948f-f033-45de-a806-a2bff2f0f021","resolution":{"observed_at":"2026-08-09T22:30:41.684127Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.09594","last_updated":"2021-03-27T14:33:40Z","snapshot_observed_at":"2026-08-08T04:14:12.725888Z","submitted_at":"2020-11-19T00:22:09Z","title":"Deep Multi-view Depth Estimation with Predicted Uncertainty","version":2},"cited_work":{"arxiv_id":"2011.09594","doi":null,"metadata_source":"pith","pith_arxiv_id":"2011.09594","snapshot_observed_at":"2026-08-09T22:30:42.042791Z","title":"Deep Multi-view Depth Estimation with Predicted Uncertainty","venue":"cs.CV","work_id":"7a64fb30-ad9a-4d25-ab68-dda526628daa","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.687707Z"},"links":{"cited_paper":"/paper/2011.09594","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:43abc5493d2a516865b5a564c120cb196f1cac06a56c39708e04de9cea1d3692","observation_id":"ef148e5e-28a1-4607-bb1b-8ed8bee162f1","resolution":{"observed_at":"2026-08-09T22:30:42.106180Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.138616Z","title":"3d gaussian splatting for real-time radiance field rendering","venue":null,"work_id":"71ba0e13-53f6-40f5-946d-c872ef3739c8","year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.691524Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:1d20182954669f3850d475df78a20e18061af10bc12cc1f5b7a3d23c62267f04","observation_id":"28163d8c-7416-44a3-87cf-18944964172c","resolution":{"observed_at":"2026-08-09T22:30:43.142093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.129234Z","title":null,"venue":null,"work_id":"43bdc0ec-0b83-4238-b160-7ad80e3c8ceb","year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.695077Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:26d9f9c60d22e779b0eadcc1f6f26588f067f68da9c60acdb0b91deae0f98832","observation_id":"16c7541b-63c5-40d9-9af9-bc985ae399ec","resolution":{"observed_at":"2026-08-09T22:30:43.132419Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-09T22:30:41.698943Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.698943Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e1c4a3e27ef3750c6cf7d90da650f651025199d4b49bd4e9d924deafc5dc055a","observation_id":"d08e76fa-5edb-42cb-8bcf-24db42f435f9","resolution":{"observed_at":"2026-08-09T22:30:41.698943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.120168Z","title":"Nor- mal assisted stereo depth estimation","venue":null,"work_id":"a3a5d4fb-33ac-40bf-afbe-5692c3572ecc","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.702522Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:884db218bc0e429ba7a08d939c03c502766c29b9d5e6b96b2227b6cd35b2662d","observation_id":"763a012b-e2ba-4aa9-8c5c-c4210eca8c5c","resolution":{"observed_at":"2026-08-09T22:30:43.123124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.111472Z","title":"Infinite nature: Perpetual view generation of natural scenes from a single image","venue":null,"work_id":"70e8e2a2-4387-4684-b428-99a727697088","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.707603Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:049bb3f1ecc5df14a0fbe021c81b8fc2c8f049b7de202ce7e749bff7f9f62db2","observation_id":"c59dafa1-66ee-4a3b-9bb0-d787cfba638e","resolution":{"observed_at":"2026-08-09T22:30:43.114387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.102818Z","title":"Zero-1-to-3: Zero-shot one image to 3d object","venue":null,"work_id":"7720f561-5754-4260-ae30-8cd5bf3c1a6a","year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.711102Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:88f563793a7f76db5b1b38ee1a6330f8edadc80d3d3e49b11f9949bab934ac1d","observation_id":"67365214-4d2c-4c1e-a027-7f9f1cd70527","resolution":{"observed_at":"2026-08-09T22:30:43.105913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03453","last_updated":"2024-04-15T10:28:44Z","snapshot_observed_at":"2026-07-06T16:15:31.848927Z","submitted_at":"2023-09-07T02:28:04Z","title":"SyncDreamer: Generating Multiview-consistent Images from a Single-view Image","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.03453","snapshot_observed_at":"2026-08-09T22:30:41.714356Z","title":"Syncdreamer: Generating multiview-consistent images from a single-view image","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.714356Z"},"links":{"cited_paper":"/paper/2309.03453","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3745fd25b7ab06cdece6a325f660e7c74ae1a002eba08b2b9320cd94458f1f82","observation_id":"0abfdf86-0f8c-4378-8655-107678b9486c","resolution":{"observed_at":"2026-08-09T22:30:41.714356Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.718169Z","title":"Decoupled weight decay regularization, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.718169Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:b0e055987f82a092695f41981b394e5c41cc3d3d02950d83286db22daceaef25","observation_id":"8bc31383-af06-4653-9e1a-a24f971c44c9","resolution":{"observed_at":"2026-08-09T22:30:41.718169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.088311Z","title":"Consistent video depth estimation","venue":null,"work_id":"b8af8b11-2705-4368-ae14-3d83b6e5c428","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.721767Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3614bc8c31a8c9326d03e6161f3902bc782eb0088ceec7314316604be8dbc79c","observation_id":"6ff23cd8-f931-4d91-b180-3de84937fda0","resolution":{"observed_at":"2026-08-09T22:30:43.091365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.078023Z","title":"Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar","venue":null,"work_id":"435669aa-9f06-4752-b5fa-dd0be4c82d69","year":2019},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.725384Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:ee91c5ffd328f5682ce85bdbcfa15cb354253271d7ea9d5f7397fb3f6f128d30","observation_id":"11dfb769-8f1c-4d06-a006-0af082d4f3ce","resolution":{"observed_at":"2026-08-09T22:30:43.081518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.067951Z","title":"NeRF: Representing scenes as neural radiance fields for view syn- thesis","venue":null,"work_id":"caef1aea-9f81-48a3-8df5-3cd58e20a45b","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.728989Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:08dd23922596ba5585c85882c552317a99e0a8b9059f61ae4b2a5002b492efdb","observation_id":"ea01283e-9adc-4154-98e4-97c9fe6731c9","resolution":{"observed_at":"2026-08-09T22:30:43.071618Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.057883Z","title":"Instant neural graphics primitives with a multiresolution hash encoding","venue":null,"work_id":"343a7eff-59d7-409c-9415-e764d6c2def9","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.733303Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:797ce551fdccf73f80fb75947ca7d72d6144e7eb55a81cc0f244ad2880be8350","observation_id":"989d0e2e-1a10-46a6-bbef-0884c9cbb520","resolution":{"observed_at":"2026-08-09T22:30:43.061640Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.047700Z","title":"Giraffe: Repre- senting scenes as compositional generative neural feature fields","venue":null,"work_id":"17daeeff-1341-4b45-8ae2-88b7730e983b","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.737172Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:05e707407cc37cf4086edddd6dc6f913ada796f744354851561dc7c3ced41652","observation_id":"b720ec6a-d0cc-43fa-a9a2-c2cb6e8b3bc1","resolution":{"observed_at":"2026-08-09T22:30:43.051197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.740755Z","title":"Barron, Ben Mildenhall, Mehdi S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.740755Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:1172456fbf6ab4590f4b0675ba1f3db19a1f81aa3de90c7a2719a93b16623213","observation_id":"c48dcd2e-60e9-494f-a322-25177c880d0f","resolution":{"observed_at":"2026-08-09T22:30:41.740755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.09748","last_updated":"2023-03-02T09:06:55Z","snapshot_observed_at":"2026-07-06T14:32:37.317828Z","submitted_at":"2022-12-19T18:59:58Z","title":"Scalable Diffusion Models with Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.09748","snapshot_observed_at":"2026-08-09T22:30:41.744405Z","title":"Scalable diffusion mod- els with transformers","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.744405Z"},"links":{"cited_paper":"/paper/2212.09748","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:20c1f6979980ddc66870f3e60908b0fd5d667861176b325be82949a0321f0c86","observation_id":"9f9ba80a-0a07-4352-85fe-bc64958e70c7","resolution":{"observed_at":"2026-08-09T22:30:41.744405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.031696Z","title":"UniDepth: Universal monocular metric depth estimation","venue":null,"work_id":"43c2f1f0-ee4c-4daf-92c3-ac002eeb677a","year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.748793Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:9b49a0b94f70097cebb931e7268bc36606890031d1c8e3a7b2bf461c7beccfe6","observation_id":"d55b69a4-5886-4bb0-9e13-944d7856a144","resolution":{"observed_at":"2026-08-09T22:30:43.035260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.022243Z","title":"Habitat-matterport 3d dataset (HM3d): 1000 large-scale 3d environments for embodied AI","venue":null,"work_id":"8e6750d7-75d4-4bab-bfd7-4eb114252dec","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.752600Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:c4ccb74a45f5e3ea0dc09f8186b088eec23a95785511c8c08a3a029edf974487","observation_id":"8a19fe01-c239-4a52-9abd-8ab11317f86d","resolution":{"observed_at":"2026-08-09T22:30:43.025507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.013052Z","title":"Zero-shot text-to-image generation","venue":null,"work_id":"49592708-b8e9-4f85-8750-15b6fe476fe9","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.755993Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:70b5f944cefa78037751ada65f05c23a328e88d600bcdd0d6f8a5fc1c975251b","observation_id":"be18c099-a0c6-4c60-b5e4-1b18243dabcc","resolution":{"observed_at":"2026-08-09T22:30:43.016159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:43.002880Z","title":"Towards robust monocu- lar depth estimation: Mixing datasets for zero-shot cross- dataset transfer","venue":null,"work_id":"1ae2b7c6-7c31-453d-ab9b-99c7d7d9f90a","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.759461Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:151761a57df4a5bdb7a69d0e3e13777cc0de5252486d1e06b3640404e4b7448b","observation_id":"0f83b3b9-eb38-4bbe-9e9d-690cac430a23","resolution":{"observed_at":"2026-08-09T22:30:43.006390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.992865Z","title":"Com- mon objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction","venue":null,"work_id":"c79ce272-6cc9-4003-a8af-6f1a2c9500eb","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.763238Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:6582f840531016f7a69e0be09fd159321337018df1e310e3de1a4cdf677e3bd1","observation_id":"6303f58a-d8c8-47bf-87c0-c4a2bb89371c","resolution":{"observed_at":"2026-08-09T22:30:42.996327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.983087Z","title":"Susskind","venue":null,"work_id":"787fd3e1-3bdc-4690-9d9d-626c8fb70357","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.767161Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:b9dbdd90bcf5ec567648b3ba19a06c3bf15e9e063129b469ddb73e1884328e9f","observation_id":"d781628d-9471-4db5-a6e0-f115cedc81b8","resolution":{"observed_at":"2026-08-09T22:30:42.986640Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.973573Z","title":"Barron, Ben Mildenhall, Pratul P","venue":null,"work_id":"59d72ef8-d739-4650-ba0c-9b61d9f41b56","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.771068Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:9fa72dc439a5d6c4b60f595053c59e524147c192dd0b4a0fe3271d18e75d4ad3","observation_id":"8e8be45a-ba9a-4fff-b78c-97892864f770","resolution":{"observed_at":"2026-08-09T22:30:42.976468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.774851Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.774851Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:e919807bf20182a4b14f6aaa27687483dcfd322c67cd192bc5e8ab3dea3cc41f","observation_id":"aebb89de-9dc5-476c-9129-9bcfccb7f214","resolution":{"observed_at":"2026-08-09T22:30:41.774851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.957281Z","title":"U- net: Convolutional networks for biomedical image segmen- tation","venue":null,"work_id":"5d20467c-fd80-4dbb-a390-016b70cc6375","year":2015},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.778758Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:122ac96bb4e600524681fc662fdafddb7991de5c815136ab8712a334c60ea052","observation_id":"6f1ade3e-8b85-4cac-a2cc-afacc71b76c7","resolution":{"observed_at":"2026-08-09T22:30:42.961118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.946931Z","title":null,"venue":null,"work_id":"a126a111-2105-46ca-996f-37e8f52a5974","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.782231Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:2892d9f5bff38d0fcd86b6fc97b60a8b632e690a88f826bbab2fb906fa86fad4","observation_id":"b46babb6-0bcf-4b04-842f-70522fafc387","resolution":{"observed_at":"2026-08-09T22:30:42.950621Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.936208Z","title":"Ze- roNVS: Zero-shot 360-degree view synthesis from a single real image","venue":null,"work_id":"3cccdb45-2dd9-4177-9c92-0a05b6192bb4","year":2024},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.785904Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:cbb1d6ee9e5a2bb36a9302958dd8f9e6f3ef5d63c5834c2898bbfb2712c53846","observation_id":"32c07f22-3a96-4247-a6de-5c9e51edec07","resolution":{"observed_at":"2026-08-09T22:30:42.940015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.926660Z","title":null,"venue":null,"work_id":"315f5856-4095-4cfc-9299-cdc9b7d71ae5","year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.789432Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:47a485aa19c71e4279fe2fa6eed7856e618703e9a1916a2f2360eec50e6d541a","observation_id":"bc4043b8-6702-4d86-9fed-7ae8e60e0938","resolution":{"observed_at":"2026-08-09T22:30:42.929413Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.918132Z","title":"Structure-from-motion revisited","venue":null,"work_id":"80162f20-4aff-4309-8003-79eec48991ed","year":2016},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.793278Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:0d622975042e17c433c81088322fea9135991964e1c083816440599a6b75be99","observation_id":"4bcb0189-aeff-40fa-9de2-c98e0a9145db","resolution":{"observed_at":"2026-08-09T22:30:42.920846Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.910152Z","title":"V oxgraf: Fast 3d-aware image syn- thesis with sparse voxel grids","venue":null,"work_id":"b603222f-92fd-4c14-90ce-7be2e2091886","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.796913Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:7efe67c9bcc307b5b897a423d20dd8474c74a6827f47ae284e4b25d01545fc50","observation_id":"9e3a5ed0-5e7e-4e60-a438-2d32f6cdf2eb","resolution":{"observed_at":"2026-08-09T22:30:42.912932Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.900160Z","title":"Learning tem- porally consistent video depth from video diffusion priors,","venue":null,"work_id":"72152484-64f3-4b39-a942-8eb1e92d949f","year":null},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.800165Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:c1b98fa9fc33ddabf468b5b59ecdf1a3b0e001dc76397f3d354507d20022dec1","observation_id":"536eb1e0-3f74-44ce-9c5d-805ebd7d087d","resolution":{"observed_at":"2026-08-09T22:30:42.903828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.889701Z","title":"Feature-metric loss for self-supervised learning of depth and egomotion","venue":null,"work_id":"c0be79b6-fe65-46ad-b8ab-f05abb73bb59","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.803387Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:97cf11c64a8072b7a8b1163df5a60f70528bc6e81b70060e04754f77c122e0df","observation_id":"47d51992-649f-4eff-81f6-be00acca997f","resolution":{"observed_at":"2026-08-09T22:30:42.893559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.879273Z","title":"Freeman, Joshua B","venue":null,"work_id":"31f53126-0475-4bde-8206-53733bccc2af","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.806767Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:f8101c20fa7ac92a20b9423e47f39c143db908a0dc265acbd609a1bdcdeb722c","observation_id":"7b3b36bb-7376-471a-afc0-01dcd93c95c8","resolution":{"observed_at":"2026-08-09T22:30:42.882972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:41.810084Z","title":"Deep unsupervised learning using nonequilibrium thermodynamics","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.810084Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:639c39817a3d344e902a208c6e184dd03b4cb1b3e651445aa34124e446bceb52","observation_id":"55012344-7136-4a54-a924-e07dbda5705d","resolution":{"observed_at":"2026-08-09T22:30:41.810084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.862451Z","title":"SimpleNeRF: Regularizing sparse input neural radiance fields with simpler solutions","venue":null,"work_id":"ff8103f8-e024-4a7b-adba-482fc9f95533","year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.813443Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:a9b15a0d95573bc9177aa99127f99fb63655d490273db8bfa4c75bbf456b60af","observation_id":"68026687-13d8-4af7-ab33-c7bb6364b677","resolution":{"observed_at":"2026-08-09T22:30:42.865904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02502","last_updated":"2022-10-05T20:19:21Z","snapshot_observed_at":"2026-07-06T10:01:50.133383Z","submitted_at":"2020-10-06T06:15:51Z","title":"Denoising Diffusion Implicit Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02502","snapshot_observed_at":"2026-08-09T22:30:41.816564Z","title":"Denois- ing diffusion implicit models","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.816564Z"},"links":{"cited_paper":"/paper/2010.02502","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:31ffdd51dc8dfcadd23a0029ad9b7d5471d01a2f52c74dce4a6b4f3f223b5e36","observation_id":"ce22e576-aaac-4d5c-9d64-4efd26d81a01","resolution":{"observed_at":"2026-08-09T22:30:41.816564Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.853800Z","title":"Sturm, N","venue":null,"work_id":"1a95ef19-c94c-4f84-a520-7106dd6ec131","year":2012},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.819787Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:75a37e70d38ef3ceee9e8478a09b3140ffa1ff246c857baad377227660239540","observation_id":"b3cc8bd5-cb8f-4cb9-af2c-3fefb9487a1d","resolution":{"observed_at":"2026-08-09T22:30:42.856578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.845235Z","title":"Generalizable patch-based neural ren- dering","venue":null,"work_id":"a9d392e4-40bf-43eb-bc21-e838b47887a2","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.822825Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:53c17a58200ab8833d8ed2fb6630094538e1b09d442af0b23692dc5dca621cec","observation_id":"039780d7-1e45-417f-a0e2-fde817d99be6","resolution":{"observed_at":"2026-08-09T22:30:42.848299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.836873Z","title":"NeuralRecon: Real-time coherent 3D re- construction from monocular video","venue":null,"work_id":"79e28fdf-da69-42ac-ac3a-b145cabfbf24","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.825640Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:651af7c1e6c3d14e3d1b4a22aea3db08660f07e6d75c7119d4cacd3d581331ed","observation_id":"3550a4cc-1a73-4c22-92a1-6473f9e5033b","resolution":{"observed_at":"2026-08-09T22:30:42.839861Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.827671Z","title":"Scalability in perception for autonomous driving: Waymo open dataset","venue":null,"work_id":"a974d781-8f7b-4a2c-ac47-c16fab5cee92","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.829524Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:308526ecda6eecb313b16fb270ad3cacf427088c6daeaaea780a61275a8f3ae2","observation_id":"609757f1-52b3-4fd2-a041-14c0d010eff5","resolution":{"observed_at":"2026-08-09T22:30:42.831172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.04807","last_updated":"2019-08-25T19:20:00Z","snapshot_observed_at":"2026-08-06T09:18:12.942546Z","submitted_at":"2018-06-13T00:51:48Z","title":"BA-Net: Dense Bundle Adjustment Network","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.04807","snapshot_observed_at":"2026-08-09T22:30:41.833232Z","title":"BA-Net: Dense bundle ad- justment network","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.833232Z"},"links":{"cited_paper":"/paper/1806.04807","citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:941e682f81deff21d7fae5aca753aa51e277c01a6c587da5c7dabc59cd97c5a9","observation_id":"45f6fba8-5705-445b-86cc-448610182131","resolution":{"observed_at":"2026-08-09T22:30:41.833232Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.817736Z","title":"Deepv2d: Video to depth with differentiable structure from motion","venue":null,"work_id":"1255bc26-a49d-4d68-89e7-a1332954d7d4","year":2020},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.836716Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:1e0fe837f2ecc452c882d535830ec5e19089550d1fb8adf6eb2dafc546d6a880","observation_id":"0ade1fb4-6ed3-4dbc-843e-2ad561d0db66","resolution":{"observed_at":"2026-08-09T22:30:42.821315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.808246Z","title":"Tenenbaum, Fr ´edo Durand, William T","venue":null,"work_id":"ca500754-5b24-4e5a-a377-137e876f3452","year":2023},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.840190Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:fdbb66e28d4ab94315a71072bbbfc3c7cd50b67da0082891a95e3e4353c40a91","observation_id":"0a99ed41-8a8f-4391-af63-17c2b76b1579","resolution":{"observed_at":"2026-08-09T22:30:42.811889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.796769Z","title":"Rtmv: A ray-traced multi-view synthetic dataset for novel view synthesis","venue":null,"work_id":"a76891bb-1f2a-40bd-8ba8-54277f8b226c","year":2022},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.843813Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:09f15f612b941e1971128fb2dcf3b0ca6f9f471466801b97c721bcfc27fd42e4","observation_id":"0ed37ca7-8d43-49cb-a905-7fc069eed3c2","resolution":{"observed_at":"2026-08-09T22:30:42.800887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.786688Z","title":"Grf: Learning a general radi- ance field for 3d representation and rendering","venue":null,"work_id":"834c43ec-d851-451f-a596-78c1e2951d09","year":2021},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.847233Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:5a7d6cbe2d7a7e970d7943eea3d235d7528f42a5cdee9c16126e3e9077b12dbc","observation_id":"c6635377-8050-4195-9621-7f1ffd7bbfb3","resolution":{"observed_at":"2026-08-09T22:30:42.789735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.777499Z","title":"Demon: Depth and motion network for learning monocular stereo","venue":null,"work_id":"bf70cc3d-a9ef-45be-b4b2-d5c9205a01fa","year":2017},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.850743Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:3a50cdb5d24d7526d6e5fdad1ac9d0bd1c65f2f0c731ac63a452086095c872d5","observation_id":"9dbf80fe-c2f6-4052-be8d-c50b74183576","resolution":{"observed_at":"2026-08-09T22:30:42.780576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T22:30:42.768447Z","title":"Neural discrete representation learning","venue":null,"work_id":"592f6ce5-62b6-4621-8a64-8a75050bfe14","year":2017},"citing_paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-09T22:30:41.854233Z"},"links":{"citing_paper":"/paper/2501.18804"},"observation_digest":"sha256:b6b541c1c830cace00849c934753e7c3fe4bf28edc91c1cc6f55c9f3265e063a","observation_id":"7149612f-4905-4715-9cbb-dd2bd9853c09","resolution":{"observed_at":"2026-08-09T22:30:42.771586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.18804","last_updated":"2025-01-30T23:43:06Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T15:32:45.488116Z","submitted_at":"2025-01-30T23:43:06Z","title":"Zero-Shot Novel View and Depth Synthesis with Multi-View Geometric Diffusion"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":64,"verified_exact":2,"verified_fuzzy":34},"total_outbound_references":125},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 100 of 125 outbound references and 1 inbound Pith citation observation for arXiv:2501.18804."}