{"as_of":"2026-08-12T16:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f6fca3d7032e90fc617831f207ff1ff80fbc2df5c6ab96ac337adb08361e9887","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T15:26:14.252873Z","state":"measured"},{"denominator":57,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":57,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2512.17143/citation-record","integrity":"/paper/2512.17143/integrity","json":"/paper/2512.17143/citation-record.json","paper":"/paper/2512.17143"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T15:26:08.598360Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:08.598360Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:bbf5109668c2b7a1e04758d45244325f34cf3731f391b305c87d7243d20b23ea","observation_id":"6cf8588e-3559-4952-ba02-29cfdc9782c3","resolution":{"observed_at":"2026-08-03T15:26:08.598360Z","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":"2026-08-03T15:26:08.643724Z","title":"Chan, Connor Z","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:08.643724Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:3c5099df7142cbe63db489638f229bc140a9f58b559c9a970a05dbe6d2d4a9d7","observation_id":"937f5351-c593-4528-ab47-2c98c64a47f6","resolution":{"observed_at":"2026-08-03T15:26:08.643724Z","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":"2026-08-03T15:26:08.704751Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:08.704751Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:80ad7b56669d410b5ed26d378301882335fd47a8d4a64a5edbb2247a27e0201e","observation_id":"933199c0-428a-4a38-8a5f-02f5b1e96057","resolution":{"observed_at":"2026-08-03T15:26:08.704751Z","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":"2026-08-03T15:26:08.797056Z","title":"Arcface: Additive angular mar- gin loss for deep face recognition.IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 44(10):5962–5979,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:08.797056Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:b928e0258dd507c74a6ee70ee3654b139387cdef32dde342e0f0872972eeed78","observation_id":"703796df-ac51-4f13-9bf2-d53e3b322516","resolution":{"observed_at":"2026-08-03T15:26:08.797056Z","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":"2026-08-03T15:26:08.874368Z","title":"A varia- tional u-net for conditional appearance and shape generation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:08.874368Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:730a4c9c956380c59ab7cc92002c9dc31028073e8483126b2f65e6dda00cd742","observation_id":"e512c0fe-a44b-465f-bf35-9e970df8d30e","resolution":{"observed_at":"2026-08-03T15:26:08.874368Z","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":"2026-08-03T15:26:08.950014Z","title":"One-shot learning for pose-guided person image synthesis in the wild","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:08.950014Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:e688b866b25245416c83212b113dba0eb790ee6b913fd667a463a32a8b740f20","observation_id":"661e7453-ceab-484c-8197-9df2db9047cf","resolution":{"observed_at":"2026-08-03T15:26:08.950014Z","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":"2026-08-03T15:26:09.024482Z","title":"Introducing gemini 2.5 flash image, our state-of-the-art image model","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.024482Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:c93e8b8f97ecbe6291106378af2a2b8cf757bf23abd5434af25195867f53cf1b","observation_id":"862f3205-e7ab-4dbf-8210-759a7f9eae51","resolution":{"observed_at":"2026-08-03T15:26:09.024482Z","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":"2026-08-03T15:26:09.115262Z","title":"Contex-human: Free- view rendering of human from a single image with texture- consistent synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.115262Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:85a6aa8e276e20b26d70a8446b40f7e7a284018992a464d23c0989b2a4531d34","observation_id":"ca00b932-3e1b-4fd0-81b7-237537f4c09f","resolution":{"observed_at":"2026-08-03T15:26:09.115262Z","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":"2026-08-03T15:26:09.189152Z","title":"Viton: An image-based virtual try-on network","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.189152Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:2f0579d4c6cbbcdfb8ed427afff38547d9c513611445adcfcb5635dec231799a","observation_id":"84c6b83d-9634-444d-ab87-0d63b47161ff","resolution":{"observed_at":"2026-08-03T15:26:09.189152Z","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":"2026-08-03T15:26:09.247299Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilib- rium.Advances in neural information processing systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.247299Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:f0c79a198d17d85b6177b435394ae38c999c89e91777c75dfbe0e76b3ddb46f6","observation_id":"e301c67e-1976-4930-bae5-b212268dc11c","resolution":{"observed_at":"2026-08-03T15:26:09.247299Z","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":"2026-08-03T15:26:09.313813Z","title":"Animate anyone: Consistent and controllable image-to-video synthesis for character animation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.313813Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:c66f4d617937146ed66b6a636c20aa00f9bdf9c9482b5129d600d7b21f8c63dd","observation_id":"08a23bb0-5c32-4f04-bf5a-00b085bedbdf","resolution":{"observed_at":"2026-08-03T15:26:09.313813Z","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":"2026-08-03T15:26:09.444662Z","title":"ARCH: Animatable Reconstruction of Clothed Humans","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.444662Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:bb37f85a58593b1e764af46fd079ef6d234e753a280ec76c5404fa49a995922d","observation_id":"74bd42a5-b98e-4876-aab2-9f631b1a51f9","resolution":{"observed_at":"2026-08-03T15:26:09.444662Z","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":"2026-08-03T15:26:09.606932Z","title":"Jafarian and H","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.606932Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:c3e0887f8dac958b88f6245fd2e0efa74722d5dd0241d58caa987f92f1d772d8","observation_id":"15e41195-75ec-44b1-bc9e-d39888a7f84e","resolution":{"observed_at":"2026-08-03T15:26:09.606932Z","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":"2026-08-03T15:26:09.734862Z","title":"Learning high fi- delity depths of dressed humans by watching social media dance videos","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.734862Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:41d816539345112b3ade52921e58e69c79ca2c609c7db7142c185e0c8b2d4a76","observation_id":"378e046b-76a8-4df3-bef3-01255ed9b5fe","resolution":{"observed_at":"2026-08-03T15:26:09.734862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10196","last_updated":"2018-02-26T15:33:34Z","snapshot_observed_at":"2026-07-06T06:06:26.276752Z","submitted_at":"2017-10-27T15:28:35Z","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10196","snapshot_observed_at":"2026-08-03T15:26:09.923850Z","title":"Progressive growing of gans for improved quality, stability, and variation.arXiv preprint arXiv:1710.10196, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:09.923850Z"},"links":{"cited_paper":"/paper/1710.10196","citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:d89f660830b679d4f5632888ed7b22095661b70786aecf7fc97f2f394b369e03","observation_id":"c5cb56d6-8662-4b96-ad9c-8634dd84de9e","resolution":{"observed_at":"2026-08-03T15:26:09.923850Z","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":"2026-08-03T15:26:10.094942Z","title":"A style-based generator architecture for generative adversarial networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.094942Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:50ee0bfb290a0ceb3e093572a846f08f61f1bbcc66a86ea99e61e1c610c3ecb7","observation_id":"a27c7fda-0512-4006-9fba-a97dbcc84b72","resolution":{"observed_at":"2026-08-03T15:26:10.094942Z","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":"2026-08-03T15:26:10.216741Z","title":"3d gaussian splatting for real-time radiance field rendering.ACM Transactions on Graphics,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.216741Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:cca6f20d7940692c8c058023c9e94b8e8a048d325d3af98466f619e310a24874","observation_id":"17f05f91-7987-4edb-bafd-a3c34de7e3ff","resolution":{"observed_at":"2026-08-03T15:26:10.216741Z","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":"2026-08-03T15:26:10.381675Z","title":"Flux.https://github.com/ black-forest-labs/flux, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.381675Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:12e3c3e76132313b84b4226ddf78d7aa1c3fc125a391937b067416ac9ea2ea2f","observation_id":"ed143387-6e3c-43a8-8eca-8b172da63f34","resolution":{"observed_at":"2026-08-03T15:26:10.381675Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.14180","last_updated":"2022-07-20T09:26:42Z","snapshot_observed_at":"2026-07-06T13:25:39.576741Z","submitted_at":"2022-06-28T17:47:53Z","title":"High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.14180","snapshot_observed_at":"2026-08-03T15:26:10.541606Z","title":"High-resolution virtual try-on with misalignment and occlusion-handled conditions.arXiv preprint arXiv:2206.14180, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.541606Z"},"links":{"cited_paper":"/paper/2206.14180","citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:0c7116ebd607a7f39f8f38a556b588df54b7803d4aaccb0f135387b5e29eec13","observation_id":"cd1ef91f-95f4-4286-b381-f0a6a9010dc2","resolution":{"observed_at":"2026-08-03T15:26:10.541606Z","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":"2026-08-03T15:26:10.674173Z","title":"Plummer, and Zhe Lin","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.674173Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:a9349412b30e11586c2346536fc8decf90ba1803c0c5cbfed563c741217ee701","observation_id":"27823f95-bd63-4ea6-bbf5-f14f112df679","resolution":{"observed_at":"2026-08-03T15:26:10.674173Z","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":"2026-08-03T15:26:10.808970Z","title":"Dense in- trinsic appearance flow for human pose transfer","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.808970Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:5b482144eddde2df9c5a99d752513e29e18b5d52dcb9343dbf1fd60897a6947b","observation_id":"4dc2ad12-abf0-4bdd-8768-28c747102ac6","resolution":{"observed_at":"2026-08-03T15:26:10.808970Z","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":"2026-08-03T15:26:10.957989Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:10.957989Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:8e247a303f77d44bea113c176d5f3a2b3d167f420e0c553966f063544fe761fa","observation_id":"4ccb9176-22fc-4dc1-bcd7-aebe900e6e1d","resolution":{"observed_at":"2026-08-03T15:26:10.957989Z","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":"2026-08-03T15:26:11.056997Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.056997Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:d3d6385f81ef5d43c33fea2505f024a4ffe2c0ef4d34adb7c7d16baaf39c8984","observation_id":"16dd3ee5-0fe0-45be-9e84-35b07fc5525e","resolution":{"observed_at":"2026-08-03T15:26:11.056997Z","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":"2026-08-03T15:26:11.181936Z","title":"Multi- focal conditioned latent diffusion for person image synthesis","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.181936Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:a2b8f2564dd8caf2bd0c35e242dc6bba32d71314b39c504ce7d7e82930c3c012","observation_id":"5f127706-4093-48fc-97c5-d22e0b406ee7","resolution":{"observed_at":"2026-08-03T15:26:11.181936Z","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":"2026-08-03T15:26:11.305106Z","title":"Deepfashion: Powering robust clothes recognition and retrieval with rich annotations","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.305106Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:9597aea5e1eb99abc2ea429e6ab967be20115b238dc1c14f711dfdc2c5ed0cf8","observation_id":"a8815822-af2a-4454-9e24-0ea989467329","resolution":{"observed_at":"2026-08-03T15:26:11.305106Z","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":"2026-08-03T15:26:11.398181Z","title":"Coarse-to-fine latent diffusion for pose- guided person image synthesis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.398181Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:98565b8a3d19c94b4e0bd81ad774db9ab8d3f5037fbd4981c5d0bd3a52d813c6","observation_id":"e4c16734-f548-4745-9697-f978d9647c7d","resolution":{"observed_at":"2026-08-03T15:26:11.398181Z","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":"2026-08-03T15:26:11.501885Z","title":"Mediapipe: A framework for perceiving and processing reality","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.501885Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:5c3df719476604d47c3573ae61283980a9ed2ff137139ddd5cc9302c34f78b24","observation_id":"0f679e61-f2d9-4534-89be-024ae2f683ac","resolution":{"observed_at":"2026-08-03T15:26:11.501885Z","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":"2026-08-03T15:26:11.581929Z","title":"Repaint: Inpainting using denoising diffusion probabilistic models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.581929Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:b856cdbcb5a60ce8e68fa91fdc21e1f09e5f8ba62f5aa9f90691c823f30835a2","observation_id":"c77a40d9-b812-403e-971f-4d0b99c1bc1d","resolution":{"observed_at":"2026-08-03T15:26:11.581929Z","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":"2026-08-03T15:26:11.655514Z","title":"Pose guided person image genera- tion","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.655514Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:3b5d5243d02fafea519f031fc390dc7f77a9204dedafa7235aba5ec0f1358159","observation_id":"500886c0-e355-4b0d-8b0f-ceb00d7cc563","resolution":{"observed_at":"2026-08-03T15:26:11.655514Z","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":"2026-08-03T15:26:11.727871Z","title":"Hpsv3: Towards wide-spectrum human preference score","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.727871Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:053959a176572e9c5d6bc0779a86d0c81ef14d260bfefd80f3a1d767e2e817e8","observation_id":"271c1c8e-113a-4f5c-984a-b1198457d2dc","resolution":{"observed_at":"2026-08-03T15:26:11.727871Z","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":"2026-08-03T15:26:11.792953Z","title":"Controllable person image synthesis with attribute-decomposed gan","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.792953Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:8c2ba88a80cc4e94ef3a2c63044200221a4c0d2990316beed9c5534cc92d0850","observation_id":"97bf33e8-5a37-4cd7-a221-d637d5940669","resolution":{"observed_at":"2026-08-03T15:26:11.792953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17113","last_updated":"2024-03-28T17:07:28Z","snapshot_observed_at":"2026-08-10T20:20:06.871596Z","submitted_at":"2023-11-28T12:05:41Z","title":"Human Gaussian Splatting: Real-time Rendering of Animatable Avatars","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17113","snapshot_observed_at":"2026-08-03T15:26:11.919035Z","title":"Human gaus- sian splatting: Real-time rendering of animatable avatars","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.919035Z"},"links":{"cited_paper":"/paper/2311.17113","citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:45c3a8671c2cf1c2e5354c59be0a30af6b2a12932ed1c1a98ce45e4bbe5182b4","observation_id":"16ef8134-226d-4584-b033-b37e206e51e4","resolution":{"observed_at":"2026-08-03T15:26:11.919035Z","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":"2026-08-03T15:26:11.985037Z","title":"Human gaussian splatting: Real-time rendering of animatable avatars","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:11.985037Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:e66085eebb4e6f304895f762ad6bfe83735b3683cf7e9f879bd8848e2463e776","observation_id":"9b282387-725e-4656-ae85-c1cdbe13d269","resolution":{"observed_at":"2026-08-03T15:26:11.985037Z","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":"2026-08-03T15:26:12.078633Z","title":"Dress Code: High- Resolution Multi-Category Virtual Try-On","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.078633Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:9c553c2a66080bff31c166f836fadcf75023f57fd8c626cbc339fc9f9b8a79a8","observation_id":"047c65b5-f961-4091-b801-03106977a7a8","resolution":{"observed_at":"2026-08-03T15:26:12.078633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-11T10:12:11.384939Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.07193","snapshot_observed_at":"2026-08-03T15:26:12.135475Z","title":"Dinov2: Learning robust visual features without supervision","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.135475Z"},"links":{"cited_paper":"/paper/2304.07193","citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:7d4f02300161d64464eccdd7a8f50bd4793cecd4b35308380c5a2c17dd92453d","observation_id":"00b330e7-f382-4294-8dd5-65e090bf706c","resolution":{"observed_at":"2026-08-03T15:26:12.135475Z","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":"2026-08-03T15:26:12.217763Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.217763Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:3ba18833a028b77ce9d83cdb96fd34b4f1019ed6ca7c8ad69ee9e6775d37e458","observation_id":"a335ef78-260a-4920-ba1b-6bbd5044fa8c","resolution":{"observed_at":"2026-08-03T15:26:12.217763Z","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":"2026-08-03T15:26:12.302419Z","title":"Li, and Ge Li","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.302419Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:fe7642e736b1234a10020a30727180e466ef4d72bdb2381350b81a5c574f3661","observation_id":"8f83a02f-7538-4efd-ba90-2a50ccfaec10","resolution":{"observed_at":"2026-08-03T15:26:12.302419Z","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":"2026-08-03T15:26:12.454119Z","title":"Pifu: Pixel-aligned implicit function for high-resolution clothed human digitiza- tion","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.454119Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:b3f68152029eb3ac1cf7b63792b43178a341f7ece2085a7d7e84cca31d7819b3","observation_id":"523691f5-ceb2-438c-87ff-e446dedcef45","resolution":{"observed_at":"2026-08-03T15:26:12.454119Z","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":"2026-08-03T15:26:12.599708Z","title":"Pifuhd: Multi-level pixel-aligned implicit function for high-resolution 3d human digitization","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.599708Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:d4839f9bfbf40e87464098ff5f0bbe08f13fcb4fcd27042c7e95fd0227fe92d8","observation_id":"ffe27ce6-fa10-4af3-bfee-f237621fed0b","resolution":{"observed_at":"2026-08-03T15:26:12.599708Z","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":"2026-08-03T15:26:12.753405Z","title":"Mohler, Larry S","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.753405Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:27651d289c21e35b4cf6172da222a08110b12e8cc3b3d1dffbbf6fd010ce7ff0","observation_id":"a21dddf5-8cb0-4b10-92ee-9ac393b6f002","resolution":{"observed_at":"2026-08-03T15:26:12.753405Z","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":"2026-08-03T15:26:12.874288Z","title":"Deformable gans for pose-based human im- age generation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.874288Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:60258467ae1a2c0247fd46fa04c1d6bdc9fabcdc291ffa5bc2b866da90bde090","observation_id":"9db6acd8-f910-4179-9c6f-09a1e9c897cc","resolution":{"observed_at":"2026-08-03T15:26:12.874288Z","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":"2026-08-03T15:26:12.987462Z","title":"First order motion model for image animation.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:12.987462Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:cd4dd122ea4425cfd18bc06b2bf496ecccd54a1333f8696609df25182a070945","observation_id":"a79eef0c-3b67-4fbe-9d49-65d9b9f21b5a","resolution":{"observed_at":"2026-08-03T15:26:12.987462Z","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":"2026-08-03T15:26:13.109833Z","title":"Toward characteristic- preserving image-based virtual try-on network","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.109833Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:381ffc3168bdcc0d72dce999d453d9628563025f299667301f3cdef900b250dc","observation_id":"3adb49c7-0ec6-4b21-aa13-2ec9e8f1232c","resolution":{"observed_at":"2026-08-03T15:26:13.109833Z","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":"2026-08-03T15:26:13.166189Z","title":"Disco: Disentangled control for referring human dance generation in real world","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.166189Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:718b20aab385af3de5d3d7a2894dcaae88d7210860b2f69dad92014fc1b8c2c5","observation_id":"60d2bdf8-abe6-4255-992a-7f4f629bc87b","resolution":{"observed_at":"2026-08-03T15:26:13.166189Z","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":"2026-08-03T15:26:13.225458Z","title":"Bovik, H.R","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.225458Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:d84c3451df277f091046f9daad89ce5ba4e4ebb88ec79d01003cff112cbc3085","observation_id":"1f8c3aa9-cd2b-4fcf-988f-2b280c2d6177","resolution":{"observed_at":"2026-08-03T15:26:13.225458Z","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":"2026-08-03T15:26:13.380954Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.380954Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:16fd20e390237a3086ecbf31221efb56a6cdd28b249240875cc88cfa5daa52a0","observation_id":"ddfe6bbb-678f-4ee8-a102-1fba93943ba1","resolution":{"observed_at":"2026-08-03T15:26:13.380954Z","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":"2026-08-03T15:26:13.453305Z","title":"Oot- diffusion: Outfitting fusion based latent diffusion for control- lable virtual try-on.AAAI, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.453305Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:47e6eae809044fc1be77ce2182ca88d8892c386b9a8eb9648cdeb122ee8aa6ca","observation_id":"f77cd8e6-5738-4f82-8bd0-9da8f574ec2c","resolution":{"observed_at":"2026-08-03T15:26:13.453305Z","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":"2026-08-03T15:26:13.550736Z","title":"Towards photo-realistic virtual try-on by adaptively generating-preserving image content","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.550736Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:19122b9163acb2401d65eb538e2be15808e58f52979314b56c7795e6d0ceb36a","observation_id":"96acfe5a-049e-497a-b014-d21b8f045778","resolution":{"observed_at":"2026-08-03T15:26:13.550736Z","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":"2026-08-03T15:26:13.596044Z","title":"3dhu- mangan: 3d-aware human image generation with 3d pose mapping","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.596044Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:26c20567a003360412d8e7170ad1b6bdb804ed103c6fdefbe07e07b4b1d188fd","observation_id":"2a89614f-4a0d-47fe-b331-7d85a3c84ad1","resolution":{"observed_at":"2026-08-03T15:26:13.596044Z","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":"2026-08-03T15:26:13.699178Z","title":"PISE: Person image synthesis and editing with decoupled gan","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.699178Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:f34122e13acca0af19293f6e779a2acac0f6c26fd89d8dab90f8d9c7d5735795","observation_id":"0cffd23e-1b99-463c-9c10-aad3e6c87ee5","resolution":{"observed_at":"2026-08-03T15:26:13.699178Z","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":"2026-08-03T15:26:13.781307Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.781307Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:b77b130050566bed672dad98a205220f3721a6d4d7b1f956b9ffd2f925093273","observation_id":"df152f04-44dc-4eb4-99a6-dd2fc269b7fa","resolution":{"observed_at":"2026-08-03T15:26:13.781307Z","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":"2026-08-03T15:26:13.846938Z","title":"Humannerf: Ef- ficiently generated human radiance field from sparse inputs","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.846938Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:d4f4d78bb44f69553082d9a1943bb5c460f4799f2cc7f254480f867314df1b7b","observation_id":"af023876-f1ee-422e-862f-477e9e4a28d1","resolution":{"observed_at":"2026-08-03T15:26:13.846938Z","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":"2026-08-03T15:26:13.916934Z","title":"Learning flow fields in attention for controllable person image generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:13.916934Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:6639bb180ae869ac9e78ae863bf46d731b9465edc45022b5cd6f01c83dc9aa1a","observation_id":"8263843b-d1d5-4342-a90b-50fd5ca8df45","resolution":{"observed_at":"2026-08-03T15:26:13.916934Z","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":"2026-08-03T15:26:14.002048Z","title":"CelebV- HQ: A large-scale video facial attributes dataset","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:14.002048Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:e164040e7820a543f4c5436fc47c635c1b2fa02c602ac139e5886106aacd4cf9","observation_id":"364acbf0-5f0e-4311-abc9-7133ce24b7d5","resolution":{"observed_at":"2026-08-03T15:26:14.002048Z","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":"2026-08-03T15:26:14.086276Z","title":"Tryondiffusion: A tale of two un- ets","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:14.086276Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:f29bbf2ec89677fc497f1b8882647f954609c3af4acad885af11e630cdd07d44","observation_id":"fc273007-7ada-431e-8435-e2a7f382a142","resolution":{"observed_at":"2026-08-03T15:26:14.086276Z","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":"2026-08-03T15:26:14.164224Z","title":"M&m vto: Multi- garment virtual try-on and editing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:14.164224Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:e85d10fb7c88418bd86da5c70d3530b30ca96be43cb69d5ac87a326548964227","observation_id":"ec786b65-1792-415b-ba70-13d935cd82df","resolution":{"observed_at":"2026-08-03T15:26:14.164224Z","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":"2026-08-03T15:26:14.252873Z","title":"Progressive pose attention transfer for person image generation","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T15:26:14.252873Z"},"links":{"citing_paper":"/paper/2512.17143"},"observation_digest":"sha256:0d6eb0ebe257f1b6501f8d545babfb3e1624ba03f3573fd3f0722d08fdc6eab2","observation_id":"a3a79e12-e3dd-4cfc-96b5-d3f627f642a8","resolution":{"observed_at":"2026-08-03T15:26:14.252873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2512.17143","last_updated":"2026-07-06T19:11:28Z","latest_version":3,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T19:46:07.647115Z","submitted_at":"2025-12-19T00:40:53Z","title":"Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":57,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":57},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2512.17143."}