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Paper Citation Record · LEDGER

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras

As of 20 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 0 inbound Pith citation observations for arXiv:2607.12993.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.12993 v2

Coverage vector

measured 96 of 96 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T06:16:28.603449Z

measured 96 of 96 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

96 of 96 outbound references displayed

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  • verified fuzzy0
  • unresolved96
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ced5a310-5a42-4ecb-9a27-e308df2806a3 · outbound

This paper cites FishRoPE: Projective Rotary Position Embeddings for Omnidirectional Visual Perception.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras FishRoPE: Projective Rotary Position Embeddings for Omnidirectional Visual Perception

Reference 1

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Observation 223bc80e-d784-421e-96f7-7bbae9513ea4 · outbound

This paper cites Depth anything in 360: Towards scale invariance in the wild.arXiv preprint arXiv:2512.22819, 2025.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth anything in 360: Towards scale invariance in the wild.arXiv preprint arXiv:2512.22819, 2025

Reference 2

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source=pdf_text observed=2026-08-02T06:16:17.725508Z digest=sha256:d792e80e6602c576ea70e6b125b5d91e24af6a471f2dd9a68e752d1d8ac3c19d

Observation d9c7a184-2f35-4ae9-886c-169aa9429bd1 · outbound

This paper cites Scenescript: Reconstructing scenes with an autoregressive structured language model.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Scenescript: Reconstructing scenes with an autoregressive structured language model

Reference 3

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source=pdf_text observed=2026-08-02T06:16:17.796378Z digest=sha256:dda3c4514cd6a317673de892fc823bc005f46417c2e4d0a99cfda7482e6dde1b

Observation f73fbb27-bb34-4e80-8d7d-13687cb6a805 · outbound

This paper cites AdaBins: Depth estimation using adaptive bins.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras AdaBins: Depth estimation using adaptive bins

Reference 4

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source=pdf_text observed=2026-08-02T06:16:17.861137Z digest=sha256:017dde5b480243649d46b3f6429e0d099432eaad7ac4c9e192ad591f9f045418

Observation e30362ff-e9ac-4c18-9c18-bec4d7d7b8cf · outbound

This paper cites ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

Reference 5

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source=pdf_text observed=2026-08-02T06:16:17.946543Z digest=sha256:341964eb504c8e57b5963529f5a79d3002315c938951dd66fe02ed48204c35f7

Observation e867f93b-61c8-428b-8c96-a445fcfcaf34 · outbound

This paper cites Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Reference 6

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source=pdf_text observed=2026-08-02T06:16:17.996556Z digest=sha256:3fa70e1191e3afbcb0b8370de826d4d3a26f15c114aacb69dda50f85c5d17e98

Observation 6b8698b3-3a0f-4a55-b9ad-17badaf16617 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 7

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source=pdf_text observed=2026-08-02T06:16:18.078184Z digest=sha256:fd989c84aa1ed8426d56698b5f735ff0e75e5148c4cec87f5df1090b09039dc3

Observation 7cbd6a71-9bf0-4288-83d5-bbdd946f4e64 · outbound

This paper cites Genie: Generative Interactive Environments.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Genie: Generative Interactive Environments

Reference 8

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source=pdf_text observed=2026-08-02T06:16:18.197866Z digest=sha256:734b4354e68e57dfce21740564ba345680380b1d9dc3c8a3f58610da35a70690

Observation 6a4d6906-3cd7-4736-9937-31680d744003 · outbound

This paper cites D\'ej\`a View: Looping Transformers for Multi-View 3D Reconstruction.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras D\'ej\`a View: Looping Transformers for Multi-View 3D Reconstruction

Reference 9

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source=pdf_text observed=2026-08-02T06:16:18.274489Z digest=sha256:26c66463831d117a5626222312ce36169e88b18166e63455814de88078d65da8

Observation 8e989bee-3dc9-45f5-a1ae-62a5f1f59892 · outbound

This paper cites Robotwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation.ArXiv, 2025.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Robotwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation.ArXiv, 2025

Reference 10

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Observation 5819bdd9-9f3d-4e05-9a30-abb2a7d49fa9 · outbound

This paper cites an unresolved cited work.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unresolved cited work

Reference 11

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Observation 4e03afd1-9b14-4110-90e5-f8770428f784 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras An image is worth 16x16 words: Transformers for image recognition at scale

Reference 12

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Observation dad5a52b-a7ea-4a13-9649-4e6cde13a424 · outbound

This paper cites Depth map prediction from a single image using a multi-scale deep network.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth map prediction from a single image using a multi-scale deep network

Reference 13

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source=pdf_text observed=2026-08-02T06:16:18.558848Z digest=sha256:f3bd427252911337f1514222be39719915701ccb99e50f3f6ef45bd22e401835

Observation 4a921439-5247-4aa5-9de5-cf4e88968f27 · outbound

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X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unresolved cited work

Reference 14

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source=pdf_text observed=2026-08-02T06:16:18.659163Z digest=sha256:fd47e4da44dd7742ceb9d14cda1186250b23c9e905778f6c5810bd1fe6f3eb4f

Observation 4b123c6d-72b6-40c9-9a7a-7f86f10db8d8 · outbound

This paper cites Extending foundational monocular depth estimators to fisheye cameras with calibration tokens.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Extending foundational monocular depth estimators to fisheye cameras with calibration tokens

Reference 15

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Observation e1c80ed5-9543-410c-be3f-11986cc4a2c8 · outbound

This paper cites an unresolved cited work.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unresolved cited work

Reference 16

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Observation 2c0e319b-74f9-4525-8df6-4aaefbab3d83 · outbound

This paper cites 3D packing for self-supervised monocular depth estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras 3D packing for self-supervised monocular depth estimation

Reference 17

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Observation 070102a5-a4ce-40e2-b2db-c17c74c887ee · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 18

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Observation 4c96e739-f4ff-43de-88fc-e808a51b8ce5 · outbound

This paper cites Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

Reference 19

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Observation ad5f3e59-ac10-4af4-ac34-3aacb165b018 · outbound

This paper cites Yeh, and Alexander G.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Yeh, and Alexander G

Reference 20

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source=pdf_text observed=2026-08-02T06:16:19.149223Z digest=sha256:4232c9e291f7d01c3927d91f8d7e9fe4d56f47fa21d841c3b028767e4e2b1b4a

Observation 4e18977f-2c6e-43aa-bdad-87603a21bf32 · outbound

This paper cites Deepmvs: Learning multi-view stereopsis.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Deepmvs: Learning multi-view stereopsis

Reference 21

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Observation e30b0ebc-1d1b-46fb-ae5d-4c1b73e58739 · outbound

This paper cites MVSAnywhere: Zero-Shot Multi-View Stereo.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras MVSAnywhere: Zero-Shot Multi-View Stereo

Reference 22

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Observation 98b4333f-c64e-4e41-ab95-47b76b8c60ad · outbound

This paper cites UniFuse: Unidirectional fusion for 360 panorama depth estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras UniFuse: Unidirectional fusion for 360 panorama depth estimation

Reference 23

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Observation c8cf0808-695c-495c-874e-c635cfc54f1d · outbound

This paper cites AnySplat: Feed-forward 3d gaussian splatting from unconstrained views.arXiv preprint arXiv:2505.23716, 2025.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras AnySplat: Feed-forward 3d gaussian splatting from unconstrained views.arXiv preprint arXiv:2505.23716, 2025

Reference 24

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Observation 87654fb5-1879-45d9-8188-b9ff7b4c7d4d · outbound

This paper cites ZipMap: Linear-Time Stateful 3D Reconstruction via Test-Time Training.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras ZipMap: Linear-Time Stateful 3D Reconstruction via Test-Time Training

Reference 25

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Observation 02e1b6e5-8e24-4403-849b-5efa5845685c · outbound

This paper cites Wid3R: Wide field-of-view 3d recon- struction via camera model conditioning.arXiv preprint arXiv:2602.05321, 2026.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Wid3R: Wide field-of-view 3d recon- struction via camera model conditioning.arXiv preprint arXiv:2602.05321, 2026

Reference 26

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source=pdf_text observed=2026-08-02T06:16:19.519742Z digest=sha256:e4de9d14fa462d02dfefa3fa25a11d27b9e177aad1b985a12f5042df8de273c0

Observation 0f9b3a08-cbc4-4463-a862-f948fcdcbe01 · outbound

This paper cites Dynamicstereo: Consistent dynamic depth from stereo videos.CVPR, 2023.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Dynamicstereo: Consistent dynamic depth from stereo videos.CVPR, 2023

Reference 27

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Observation d68423b7-cb5e-4399-9cc0-8c7ce7116122 · outbound

This paper cites MapAnything: Universal Feed-Forward Metric 3D Reconstruction.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras MapAnything: Universal Feed-Forward Metric 3D Reconstruction

Reference 28

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Observation 2e77b33e-a0fc-441c-8aae-8fa84bdfebd5 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras OpenVLA: An Open-Source Vision-Language-Action Model

Reference 29

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Observation 06da7151-1cd9-412d-8ac6-841e63691962 · outbound

This paper cites From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

Reference 30

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Observation d8434053-2829-494c-9be7-243edd64c0a6 · outbound

This paper cites Grounding Image Matching in 3D with MASt3R.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Grounding Image Matching in 3D with MASt3R

Reference 31

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Observation 6728fbae-6457-4252-b322-289479275469 · outbound

This paper cites Economics of Innovation and Perceptions of Renewed Education and Curriculum Design in Bangladesh.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Economics of Innovation and Perceptions of Renewed Education and Curriculum Design in Bangladesh

Reference 32

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Observation dedf4677-8079-41f0-bf7f-5cb7ae44019b · outbound

This paper cites CasOmniMVS: Cascade omnidirectional depth estimation with dynamic spherical sweeping.Applied Sciences, 2024.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras CasOmniMVS: Cascade omnidirectional depth estimation with dynamic spherical sweeping.Applied Sciences, 2024

Reference 33

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Observation 76323706-9e57-401f-bfdc-662a27433f08 · outbound

This paper cites Megadepth: Learning single-view depth prediction from internet photos.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Megadepth: Learning single-view depth prediction from internet photos

Reference 34

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Observation 3f673702-265b-4219-9f48-26c18d73a366 · outbound

This paper cites PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation

Reference 35

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source=pdf_text observed=2026-08-02T06:16:20.398778Z digest=sha256:b2c55394e2ac1d1e414ba5436ea97a07f1319389e0c32f12835edd0c7429a443

Observation dc59bf75-969f-489b-a490-27b072f4edd5 · outbound

This paper cites Language as prior, vision as calibration: Metric scale recovery for monocular depth estimation.arXiv preprint arXiv:2601.01457, 2026.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Language as prior, vision as calibration: Metric scale recovery for monocular depth estimation.arXiv preprint arXiv:2601.01457, 2026

Reference 36

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source=pdf_text observed=2026-08-02T06:16:20.604496Z digest=sha256:5b479ff784066a8b53b4b87c05223a59ef851ce44388b0fc05a0d4b82e37b402

Observation b6beeac4-5de5-4024-ab78-c18098daa772 · outbound

This paper cites KITTI-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras KITTI-360: A novel dataset and benchmarks for urban scene understanding in 2d and 3d

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source=pdf_text observed=2026-08-02T06:16:20.716210Z digest=sha256:854855430339676261caec694f38803826d6974042f909cffba1376061f797b5

Observation 0a82e915-92af-4141-8b49-56fa22f6c833 · outbound

This paper cites Depth Anything 3: Recovering the Visual Space from Any Views.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth Anything 3: Recovering the Visual Space from Any Views

Reference 38

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source=pdf_text observed=2026-08-02T06:16:20.889034Z digest=sha256:cd467308b7b10873df5bc8b0e8acaab1698ae826c7c6c9bd91a34e03f3c6cc23

Observation 84767741-d868-440e-a1c2-3b2469fa2183 · outbound

This paper cites Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation

Reference 39

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source=pdf_text observed=2026-08-02T06:16:21.014814Z digest=sha256:006ca530fc5a261abf4a02ecde66bbfa815882dca0f6d94b4ff76f6d5b7b6dce

Observation 9c55c395-a61a-4eb6-9f97-5cfde1eae1e2 · outbound

This paper cites Depth any panoramas: A foundation model for panoramic depth estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth any panoramas: A foundation model for panoramic depth estimation

Reference 40

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source=pdf_text observed=2026-08-02T06:16:21.137189Z digest=sha256:a453b8c19df1d564ea5e73851872335f3493fe0e175b293b2e70a64c5857e5da

Observation e4debc0c-45f4-4fd2-a761-0f3a2b1700a5 · outbound

This paper cites DL3DV-10K: A large-scale scene dataset for deep learning-based 3d vision.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras DL3DV-10K: A large-scale scene dataset for deep learning-based 3d vision

Reference 41

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source=pdf_text observed=2026-08-02T06:16:21.306242Z digest=sha256:0df71c403c902b088c9f913968f806d5894878e8db866c762845bb92fcf38625

Observation 23cfa0b8-1f8d-4949-8a18-5a3d1b78d156 · outbound

This paper cites an unresolved cited work.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unresolved cited work

Reference 42

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source=pdf_text observed=2026-08-02T06:16:21.394303Z digest=sha256:e714ff3b146b9cdf3d6bdcbe0d06eb84d4faad196483d34ce9621d6a21626937

Observation 95f750f2-870b-4202-93fc-e6bb583f9db7 · outbound

This paper cites Mapillary planet-scale depth dataset.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Mapillary planet-scale depth dataset

Reference 43

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source=pdf_text observed=2026-08-02T06:16:21.576918Z digest=sha256:11f3758e6f1f9d5833b7d816a7bba234fcf9256d678a95cb0ce25a25d9aac1d1

Observation a164b1e4-dae6-4493-a1da-a23c627ac8f7 · outbound

This paper cites WideDepth: Millimeter-Accurate Benchmark for Fisheye Depth Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras WideDepth: Millimeter-Accurate Benchmark for Fisheye Depth Estimation

Reference 44

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source=pdf_text observed=2026-08-02T06:16:21.716948Z digest=sha256:fb69697f20f2e6ba778bca3a42da37fb7b076455ff640aebdeabea39dd94ebc6

Observation 61114cb9-13a7-4c02-8c3f-c475b0e56a11 · outbound

This paper cites SimpleProc: Fully Procedural Synthetic Data from Simple Rules for Multi-View Stereo.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras SimpleProc: Fully Procedural Synthetic Data from Simple Rules for Multi-View Stereo

Reference 45

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source=pdf_text observed=2026-08-02T06:16:21.902206Z digest=sha256:a0ef1a908e44fc60971366058c9f48eeb8dc7b6bb5c3ff98638328ebbf0325d2

Observation 21d0f27b-5dae-400d-8a59-853557aa44d1 · outbound

This paper cites Spring: A high-resolution high-detail dataset and benchmark for scene flow, optical flow and stereo.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Spring: A high-resolution high-detail dataset and benchmark for scene flow, optical flow and stereo

Reference 46

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source=pdf_text observed=2026-08-02T06:16:22.053019Z digest=sha256:18093ce66362c1a3b3e9fe17cc51b480d8f20c4fd39bc4afed9d9cb4e1143723

Observation 79c6a9b9-e086-4744-85d9-9667da03af0f · outbound

This paper cites an unresolved cited work.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unresolved cited work

Reference 47

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source=pdf_text observed=2026-08-02T06:16:22.263868Z digest=sha256:b2e3bbc49902958acbdba233e14c25a538e4884f44a83e7d4cb8a5396fd298c0

Observation 6359fb74-272b-4df7-9b2c-c2fd5475a90d · outbound

This paper cites V o-dp: Semantic-geometric adaptive diffusion policy for vision-only robotic manipulation.ArXiv, 2025.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras V o-dp: Semantic-geometric adaptive diffusion policy for vision-only robotic manipulation.ArXiv, 2025

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source=pdf_text observed=2026-08-02T06:16:22.416566Z digest=sha256:e3733fa99de35e6b9e5f9ac15bbed2d67512226bb9e829f2c66655b71f9df5e7

Observation 962923bb-da67-481d-a2aa-ed4bad23391e · outbound

This paper cites Octo: An Open-Source Generalist Robot Policy.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Octo: An Open-Source Generalist Robot Policy

Reference 49

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source=pdf_text observed=2026-08-02T06:16:22.583531Z digest=sha256:f29208f6b547d612b1b54771b4e9bd695013e208dd942f8269fa8e8c08fb7ee4

Observation 7983e305-8639-4ba8-be3f-e31b0e6537c0 · outbound

This paper cites DINOv2: Learning robust visual features without supervision.Transactions on Machine Learning Research (TMLR), 2024.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras DINOv2: Learning robust visual features without supervision.Transactions on Machine Learning Research (TMLR), 2024

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source=pdf_text observed=2026-08-02T06:16:22.809566Z digest=sha256:f8e57b44e37b00b27465c52198aca3d8c54135813f8405997eaf135000e0a7f1

Observation 93db722c-5e2b-4df7-8b61-fddd2fa1d125 · outbound

This paper cites TartanGround: A large-scale dataset for ground robot perception and navigation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras TartanGround: A large-scale dataset for ground robot perception and navigation

Reference 51

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source=pdf_text observed=2026-08-02T06:16:22.917292Z digest=sha256:b1f8cd8128203dc7e456002931d91088a29692b6d4a0ec4d94dcd528328fc40e

Observation 12c6263d-e1ff-4c54-bf77-1d31fe90e9bb · outbound

This paper cites Scalable diffusion models with transformers.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Scalable diffusion models with transformers

Reference 52

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source=pdf_text observed=2026-08-02T06:16:23.077606Z digest=sha256:30bec9fa9018361fdb659abe57a268990ac9f6ef2cd864acb8fd64d0b8e5b8a0

Observation 0713ca99-8883-4123-9608-84cdeb5c09f9 · outbound

This paper cites UniDepth: Universal monocular metric depth estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras UniDepth: Universal monocular metric depth estimation

Reference 53

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source=pdf_text observed=2026-08-02T06:16:23.180196Z digest=sha256:8544edaee9991fb70a91100043ebd9c22e556aeaf40c74e0fcdb03a1cc713a1f

Observation 87a4097f-76f1-411b-83f3-28324e130ad2 · outbound

This paper cites UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Reference 54

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source=pdf_text observed=2026-08-02T06:16:23.295803Z digest=sha256:5f02fcf2498764ae0c9804633563c0d3eed831165228ffa6ffe9f35832ec0dbf

Observation 5960358c-2703-41b6-8264-90943cdd1781 · outbound

This paper cites UniK3D: Universal Camera Monocular 3D Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras UniK3D: Universal Camera Monocular 3D Estimation

Reference 55

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source=pdf_text observed=2026-08-02T06:16:23.406749Z digest=sha256:41cfd809eb29fb82853e41372e00798c03e5557aba894237deac3e47b7f06158

Observation 1f8ddc2a-9c83-4ea2-acfd-e4a75450f21d · outbound

This paper cites Learning transferable visual models from natural language supervision.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Learning transferable visual models from natural language supervision

Reference 56

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source=pdf_text observed=2026-08-02T06:16:23.542320Z digest=sha256:84d7f8e9f73e8a14b3826ff6b149dbea722c04f51d599c0e7629bb948a2d455b

Observation d09f3f5d-0aa5-4b52-a556-af5487082b67 · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020

Reference 57

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source=pdf_text observed=2026-08-02T06:16:23.648316Z digest=sha256:59d3831d02309f8264ce7442b844263f15bd96f8ff9445079668d6ef9b87a282

Observation 43f1f6c8-9858-4dca-83a9-4d84454be433 · outbound

This paper cites Vision transformers for dense prediction.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Vision transformers for dense prediction

Reference 58

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source=pdf_text observed=2026-08-02T06:16:23.691719Z digest=sha256:d452665e464d27c71ceed14af12f483af942ab369d5a8f6bb3f7b66305907958

Observation 952b464b-c93e-4a98-adc0-30364dd580dd · outbound

This paper cites Sch¨onberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Sch¨onberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger

Reference 59

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source=pdf_text observed=2026-08-02T06:16:23.766760Z digest=sha256:6168cba6d953fba6b90879847b7fe90bd4a67b20cb81cb67f6ae1bf2bb85c03b

Observation 0823d04b-b4be-47e0-b99b-3b5d3c06a1fe · outbound

This paper cites PanoFormer: Panorama transformer for indoor 360 depth estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras PanoFormer: Panorama transformer for indoor 360 depth estimation

Reference 60

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source=pdf_text observed=2026-08-02T06:16:23.828708Z digest=sha256:78fa2872bedc3136834cea845f5c99f75a7920b7ce3b1073e4388a6bdf214c7b

Observation 3ec6110c-7b25-4f3d-9f90-8f17e7d01cc4 · outbound

This paper cites an unresolved cited work.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unresolved cited work

Reference 61

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source=pdf_text observed=2026-08-02T06:16:23.933724Z digest=sha256:a1562e048928393b4a5bafa1cfe36c8fce12a107f8ad1540b58443c4198d7138

Observation 5b6dcfc0-934f-4aea-80e6-a535aa652f7c · outbound

This paper cites RoFormer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras RoFormer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063, 2024

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source=pdf_text observed=2026-08-02T06:16:24.071140Z digest=sha256:ae2ca3e622da2c00a6602f2f35b7b5b193fec194cacab1c05c53da77556db5cd

Observation 5f334ee0-50aa-44ca-a0e9-092693c3fbe6 · outbound

This paper cites HoHoNet: 360 indoor holistic understanding with latent horizontal features.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras HoHoNet: 360 indoor holistic understanding with latent horizontal features

Reference 63

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source=pdf_text observed=2026-08-02T06:16:24.164624Z digest=sha256:2941276617e68775e53ae00931d8667e79fb59b5fe08792233c3e3b934c346da

Observation 9c0ccbc7-9622-492e-883c-840bc006a42a · outbound

This paper cites Distortion-aware convolutional filters for dense prediction in panoramic images.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Distortion-aware convolutional filters for dense prediction in panoramic images

Reference 64

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source=pdf_text observed=2026-08-02T06:16:24.354890Z digest=sha256:440d7892583a99832dc35f72549bfb6a4046636236c17410a48fad5c81eddb66

Observation cd6dbca4-4b25-47d1-ba62-d26c34874829 · outbound

This paper cites Smd-nets: Stereo mixture density networks.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Smd-nets: Stereo mixture density networks

Reference 65

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source=pdf_text observed=2026-08-02T06:16:24.508013Z digest=sha256:232c44dad3b10e8ce94e64445f434808b7529778f1ae6b40272b2e68ff40c66a

Observation 856b435e-7375-4487-a116-860fe9738b7b · outbound

This paper cites Generative camera dolly: Extreme monocular dynamic novel view synthesis.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Generative camera dolly: Extreme monocular dynamic novel view synthesis

Reference 66

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source=pdf_text observed=2026-08-02T06:16:24.715662Z digest=sha256:7a456bf9cf4d73f454635dd524ab4d743868ee516c39e9c48df63675427eb45a

Observation 4326b5b7-9881-43f8-b4fe-af9fe951f8fb · outbound

This paper cites BiFuse: Monocular 360 depth estimation via bi- projection fusion.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras BiFuse: Monocular 360 depth estimation via bi- projection fusion

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source=pdf_text observed=2026-08-02T06:16:24.858038Z digest=sha256:892a849cf48124bc8c9532e0d301d2c0fc696c99d973fa2a9d3f0896dbd0b17e

Observation 50201759-302e-4e3d-955c-449ba58bd393 · outbound

This paper cites V oyager: An open-ended embodied agent with large language models.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras V oyager: An open-ended embodied agent with large language models

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source=pdf_text observed=2026-08-02T06:16:25.008683Z digest=sha256:e6a8b32b344f4187c4563db876505a315079320de239b37bcfe98b81a7f3df0f

Observation ebf4666c-d79f-4930-9b9d-4e6c8bfa0679 · outbound

This paper cites 3D Reconstruction with Spatial Memory.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras 3D Reconstruction with Spatial Memory

Reference 69

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source=pdf_text observed=2026-08-02T06:16:25.146788Z digest=sha256:a53c5bbbfba20d670a613d5aae1fd34ec70bfc1477656643850d825d2738c5f8

Observation dff690a6-b741-4831-9315-2e53e092375d · outbound

This paper cites VGGT: Visual Geometry Grounded Transformer.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras VGGT: Visual Geometry Grounded Transformer

Reference 70

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source=pdf_text observed=2026-08-02T06:16:25.268319Z digest=sha256:51accde941000d5665e3a920a1355cced0ce43888ed4b6aa920c05bb0de71469

Observation d1052658-8d09-476a-9fc3-cd9028f8267b · outbound

This paper cites VGGT-$\Omega$.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras VGGT-$\Omega$

Reference 71

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source=pdf_text observed=2026-08-02T06:16:25.342379Z digest=sha256:e703a4dd8f0845ff2fe62f224befcb7fa364cf455b97fc5f6fe3d71948c92a7d

Observation 27cc364d-e1ef-48d4-b909-37f42c5afc66 · outbound

This paper cites A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots

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source=pdf_text observed=2026-08-02T06:16:25.442313Z digest=sha256:e7be4f6512e6fce449b2575d130dcb962e8f6577994ff58030e5d14ff876100a

Observation 16fb3fe6-5aff-4e98-b84a-ec0bc6784d7e · outbound

This paper cites Unsupervised OmniMVS: Efficient Omnidirectional Depth Inference via Establishing Pseudo-Stereo Supervision.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Unsupervised OmniMVS: Efficient Omnidirectional Depth Inference via Establishing Pseudo-Stereo Supervision

Reference 73

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source=pdf_text observed=2026-08-02T06:16:25.555720Z digest=sha256:7d250c8bef80bd3dc0d37d93c1d512518d1d39919863534fd8bb50c5717919a3

Observation 5b484509-dbb2-4d78-93a1-eb1fe71312e2 · outbound

This paper cites MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision

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source=pdf_text observed=2026-08-02T06:16:25.668451Z digest=sha256:0eebc3c1a5cd80e9ae4995888f491ae7181a1bd697b93c3c1ca24ddf1067d79b

Observation 8ab89b35-63a4-4182-ac03-1e2cbb379142 · outbound

This paper cites MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details

Reference 75

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source=pdf_text observed=2026-08-02T06:16:25.775240Z digest=sha256:a0b6a586cf62f087435cd2f2716c716a3fc87dcc099434d83075aedd7ad4a9b0

Observation 415a2dbc-9a89-4baa-a62d-9216809abfcf · outbound

This paper cites AnchorD: Metric Grounding of Monocular Depth Using Factor Graphs.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras AnchorD: Metric Grounding of Monocular Depth Using Factor Graphs

Reference 76

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source=pdf_text observed=2026-08-02T06:16:25.962478Z digest=sha256:19990cca7063c7bd6f679edbe89861b01ba67d10eb6961e047c7e71c273a4f59

Observation 9fc4ae17-572b-49ca-915d-1502717dbdc1 · outbound

This paper cites MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources

Reference 77

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source=pdf_text observed=2026-08-02T06:16:26.106940Z digest=sha256:5a7435e2c7599355acef02288055c44f949b98b3870261115c85741431ca095a

Observation 8d16f647-fd50-4d9b-a6c1-cd04d2482474 · outbound

This paper cites DUSt3R: Geometric 3D Vision Made Easy.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras DUSt3R: Geometric 3D Vision Made Easy

Reference 78

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source=pdf_text observed=2026-08-02T06:16:26.180638Z digest=sha256:8830117b8f56836c242c6ed4fd3a01971919d78fb2a03258bcc0f1dd808ea9f7

Observation e52219a5-f04f-455d-8a85-eb2465e21346 · outbound

This paper cites $\pi^3$: Permutation-Equivariant Visual Geometry Learning.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras $\pi^3$: Permutation-Equivariant Visual Geometry Learning

Reference 79

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source=pdf_text observed=2026-08-02T06:16:26.305634Z digest=sha256:3925a3195f04b19f28a58faafbec5cc5af2e0e84259032f4e18af324e77c4663

Observation 4f790ebd-98de-4039-b857-04c25a693e2c · outbound

This paper cites Omnimvs: End-to-end learning for omnidirectional stereo matching.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Omnimvs: End-to-end learning for omnidirectional stereo matching

Reference 80

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source=pdf_text observed=2026-08-02T06:16:26.515655Z digest=sha256:37353b909345ba703f1b9124a98e5a62a9bdbedf153578e83e2842877e4a5747

Observation a3278737-b7d5-4d3c-817a-9824707866ea · outbound

This paper cites Scal3R: Scalable Test-Time Training for Large-Scale 3D Reconstruction.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Scal3R: Scalable Test-Time Training for Large-Scale 3D Reconstruction

Reference 81

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source=pdf_text observed=2026-08-02T06:16:26.706627Z digest=sha256:827ce4e4aada0d73872256851276293b6046d14433e226d879cd4ef35f0144a6

Observation 24e90624-dbd8-46d5-ac7d-e6e6250d2afe · outbound

This paper cites DA2: Depth anything in any direction.arXiv preprint arXiv:2509.26618, 2025.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras DA2: Depth anything in any direction.arXiv preprint arXiv:2509.26618, 2025

Reference 82

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source=pdf_text observed=2026-08-02T06:16:26.838245Z digest=sha256:6a694e30ae9e28f5742740a679aae806af9e0dc433205ac2354174b53df27734

Observation a65f1737-2f94-4792-a7bf-018b2236f64f · outbound

This paper cites Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass

Reference 83

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source=pdf_text observed=2026-08-02T06:16:26.979184Z digest=sha256:3665bff49ed712ca0db1d3143da277346919b52d74f23a0cb75e4947b3452aca

Observation faa3249b-8977-4d61-b78b-122de9f1d317 · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth anything: Unleashing the power of large-scale unlabeled data

Reference 84

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source=pdf_text observed=2026-08-02T06:16:27.093400Z digest=sha256:073db3a88656d9afc40e8bf30052e3bd57af31abe1fa40cc56552b518494119c

Observation 743b3580-074c-45b1-ae59-2e7efc9340ac · outbound

This paper cites Depth Anything V2.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth Anything V2

Reference 85

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source=pdf_text observed=2026-08-02T06:16:27.167818Z digest=sha256:5c581e1df9680ba7436a790a20d9c26146b015aafd49a0a875e1b37ea36a1af2

Observation 7b749165-ee2a-424f-81b7-5157dd18f758 · outbound

This paper cites Video Depth Anything: Consistent Depth Estimation for Super-Long Videos.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Video Depth Anything: Consistent Depth Estimation for Super-Long Videos

Reference 86

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source=pdf_text observed=2026-08-02T06:16:27.239660Z digest=sha256:fd952a0a82b38a37a6be8c6ddd07981597f93169a48aac36759c32ef2658e6b3

Observation 48a997de-9c46-4ee8-8309-4fd3ac700091 · outbound

This paper cites Blendedmvs: A large-scale dataset for generalized multi-view stereo networks.Computer Vision and Pattern Recognition (CVPR), 2020.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Blendedmvs: A large-scale dataset for generalized multi-view stereo networks.Computer Vision and Pattern Recognition (CVPR), 2020

Reference 87

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source=pdf_text observed=2026-08-02T06:16:27.345054Z digest=sha256:9491ae54e1b965e92a3f2ca7ad5d7b1ba2313ffcf09fcb7997988a56556a6c3d

Observation 406387ae-9e59-49c7-a507-887fcb49f4ec · outbound

This paper cites ScanNet++: A high-fidelity dataset of 3d indoor scenes.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras ScanNet++: A high-fidelity dataset of 3d indoor scenes

Reference 88

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source=pdf_text observed=2026-08-02T06:16:27.476260Z digest=sha256:5def2baf8a6ac97246883c9ce9c5a08f5fbd683cd6ccb890a03cbe9447558fec

Observation 5c8fcad7-c701-4ddc-a9e0-6e99c03b4047 · outbound

This paper cites Metric3D: Towards zero-shot metric 3d prediction from a single image.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Metric3D: Towards zero-shot metric 3d prediction from a single image

Reference 89

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source=pdf_text observed=2026-08-02T06:16:27.618183Z digest=sha256:384585db03b7e2feec712e02881391d89fc7916a2cba6d376724ddfc3a03fe3e

Observation 5cf8634a-f15d-4b23-ba73-5f01150dadb4 · outbound

This paper cites NeWCRFs: Neural window fully-connected crfs for monocular depth estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras NeWCRFs: Neural window fully-connected crfs for monocular depth estimation

Reference 90

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source=pdf_text observed=2026-08-02T06:16:27.766656Z digest=sha256:de241389d39d2346006076389ce2e4553516dad78bf05f2c44b1238c78e2ba2a

Observation d4cbefa4-0d25-4a73-b816-787d1f6e7505 · outbound

This paper cites EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation

Reference 91

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source=pdf_text observed=2026-08-02T06:16:27.843888Z digest=sha256:1a65df4e72dc7d4d7536e1dc3979c14598512788d72c13bed0604c22ac73150e

Observation 3a5d973c-b9f5-42c6-b238-bd883bd6dc27 · outbound

This paper cites Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera

Reference 92

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source=pdf_text observed=2026-08-02T06:16:28.030916Z digest=sha256:a39c7038212a4d5638fc965693fbc561714fd22d3fc57b213d7918ff01e1db1b

Observation e4f68a8d-c76d-460c-8eca-5a5a8ab770ff · outbound

This paper cites MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion

Reference 93

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source=pdf_text observed=2026-08-02T06:16:28.142224Z digest=sha256:a0e9ee13ebdd2d01aca7b732277ea72c4a47e35cde7633fb8517143d8168c1de

Observation f3279a88-8887-4497-a369-21587efd7acc · outbound

This paper cites StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views

Reference 94

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source=pdf_text observed=2026-08-02T06:16:28.252718Z digest=sha256:a06db8482aa0a2ac571967af3648d415c083da3f86e24875b4bfe1753ca2bb3c

Observation 789a1592-39bb-4295-86fc-7997507182d1 · outbound

This paper cites 3D-VLA: A 3d vision-language-action generative world model.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras 3D-VLA: A 3d vision-language-action generative world model

Reference 95

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source=pdf_text observed=2026-08-02T06:16:28.460825Z digest=sha256:4f9936d8bfa397829566da405f2c8d30c1ec376879b94ab4075762b8f24d8e68

Observation 21f4ecb0-c4a9-4fb0-babc-3c52d0743d4b · outbound

This paper cites OccWorld: Learning a 3d occupancy world model for autonomous driving.

X-Lens: Real-Time Metric Depth Estimation with Heterogeneous Cameras OccWorld: Learning a 3d occupancy world model for autonomous driving

Reference 96

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source=pdf_text observed=2026-08-02T06:16:28.603449Z digest=sha256:419f04a4c7a381a00ac6c4d8abeeeffc09825191144df6b6f4cf58f17730c56b

Pith citing papers

No inbound Pith citation observations are available.