Paper Citation Record · LEDGER

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 49 inbound Pith citation observations for arXiv:2401.10891.

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

pith.paper-citation-record.v1
2401.10891 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 49 of 49 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:27:05.298307Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T00:06:37.938145Z

Reference resolution

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0cb7c469-983c-4b33-aadc-0fcd59a78d34 · inbound

Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation cites this paper.

Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:13:55.743195Z

Source-reported events for the cited work

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Observation e4b42036-99fd-4194-adb7-8a336829c660 · inbound

Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting cites this paper.

Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 48

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Source-reported events for the cited work

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Observation 732490d1-7a9a-4d32-b520-e52044d3a79b · inbound

DissolveStereo: Coarse Depth Injection for Zero-Shot Stereo Video Generation cites this paper.

DissolveStereo: Coarse Depth Injection for Zero-Shot Stereo Video Generation Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:18:13.901834Z

Source-reported events for the cited work

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Observation d8caf0c0-9521-4c67-a38b-d3a1b39f78f4 · inbound

AGS-Mesh: Adaptive Gaussian Splatting and Meshing with Geometric Priors for Indoor Room Reconstruction Using Smartphones cites this paper.

AGS-Mesh: Adaptive Gaussian Splatting and Meshing with Geometric Priors for Indoor Room Reconstruction Using Smartphones Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 53

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Source-reported events for the cited work

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Observation cea09e62-5f0c-458d-9086-83fb262d83a8 · inbound

Amodal Depth Anything: Amodal Depth Estimation in the Wild cites this paper.

Amodal Depth Anything: Amodal Depth Estimation in the Wild Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T23:41:19.010134Z

Source-reported events for the cited work

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Observation 88144c07-83ca-4b92-88d4-553546b535c1 · inbound

From an Image to a Scene: Learning to Imagine the World from a Million 360 Videos cites this paper.

From an Image to a Scene: Learning to Imagine the World from a Million 360 Videos Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T18:33:51.684925Z

Source-reported events for the cited work

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Observation a1d5f027-a5c3-4a36-9e8e-bdce06b83400 · inbound

T-SVG: Text-Driven Stereoscopic Video Generation cites this paper.

T-SVG: Text-Driven Stereoscopic Video Generation Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 27

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Source-reported events for the cited work

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Observation 2032c7a3-4ad7-4ace-81f0-137ae5202f6d · inbound

MambaPro: Multi-Modal Object Re-Identification with Mamba Aggregation and Synergistic Prompt cites this paper.

MambaPro: Multi-Modal Object Re-Identification with Mamba Aggregation and Synergistic Prompt Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-11T15:47:36.598818Z

Source-reported events for the cited work

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Observation ae5126b8-d01b-4e76-b15e-40c68ade444d · inbound

RoMeO: Robust Metric Visual Odometry cites this paper.

RoMeO: Robust Metric Visual Odometry Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T14:55:03.266694Z

Source-reported events for the cited work

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Observation 831b6978-3596-416b-8af8-79b44efecac4 · inbound

ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Science cites this paper.

ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Science Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 141

Resolution: unresolved; no resolver link, observed 2026-08-11T04:57:32.262954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae883fcb-4fa9-4f58-9b55-c06fbbb0f221 · inbound

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

PatchRefiner V2: Fast and Lightweight Real-Domain High-Resolution Metric Depth Estimation Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-10T22:39:32.655540Z

Source-reported events for the cited work

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Observation 4f032094-54a7-4b91-b588-b8c0430aed81 · inbound

Tech Report: Divide and Conquer 3D Real-Time Reconstruction for Improved IGS cites this paper.

Tech Report: Divide and Conquer 3D Real-Time Reconstruction for Improved IGS Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T22:51:16.567674Z

Source-reported events for the cited work

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Observation bed563df-2163-4585-8102-836709a7dabb · inbound

Generative Physical AI in Vision: A Survey cites this paper.

Generative Physical AI in Vision: A Survey Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 236

Resolution: unresolved; no resolver link, observed 2026-08-10T18:53:00.919246Z

Source-reported events for the cited work

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Observation 3a41c30f-7322-4835-bfaa-febf22638fc2 · inbound

Enhancing Monocular Depth Estimation with Multi-Source Auxiliary Tasks cites this paper.

Enhancing Monocular Depth Estimation with Multi-Source Auxiliary Tasks Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T16:50:11.260964Z

Source-reported events for the cited work

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Observation b8e4e1ee-c8d6-4665-a001-d17ba0dfb875 · inbound

RoboGrasp: A Universal Grasping Policy for Robust Robotic Control cites this paper.

RoboGrasp: A Universal Grasping Policy for Robust Robotic Control Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T06:05:09.964738Z

Source-reported events for the cited work

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Observation 6487b03d-0df8-41cb-8ecd-dcae0af56087 · inbound

All-in-One Image Compression and Restoration cites this paper.

All-in-One Image Compression and Restoration Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T04:17:43.921004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e77f8d4d-5adf-4bce-bfe7-aca97bd38409 · inbound

LeAP: Consistent multi-domain 3D labeling using Foundation Models cites this paper.

LeAP: Consistent multi-domain 3D labeling using Foundation Models Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T00:21:15.467101Z

Source-reported events for the cited work

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Observation fc7f01ee-d954-4836-994a-85a2e3552667 · inbound

Lightweight RGB-D Salient Object Detection from a Speed-Accuracy Tradeoff Perspective cites this paper.

Lightweight RGB-D Salient Object Detection from a Speed-Accuracy Tradeoff Perspective Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T23:27:05.298307Z

Source-reported events for the cited work

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Observation 9a002863-f443-4a03-bf99-c4e50ebedfc0 · inbound

Is Semantic SLAM Ready for Embedded Systems ? A Comparative Survey cites this paper.

Is Semantic SLAM Ready for Embedded Systems ? A Comparative Survey Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 123

Resolution: unresolved; no resolver link, observed 2026-08-15T20:38:21.459542Z

Source-reported events for the cited work

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Observation 97cd2411-8dfd-4713-b1b4-d4c0d274e3f2 · inbound

Towards In-the-wild 3D Plane Reconstruction from a Single Image cites this paper.

Towards In-the-wild 3D Plane Reconstruction from a Single Image Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T11:27:22.551197Z

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Observation 6732de36-5603-4a24-8591-10bd181f752a · inbound

Generating 6DoF Object Manipulation Trajectories from Action Description in Egocentric Vision cites this paper.

Generating 6DoF Object Manipulation Trajectories from Action Description in Egocentric Vision Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-07T11:03:01.873084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec5623ee-2697-4d0a-9f03-2508a90841b1 · inbound

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study cites this paper.

Challenging Vision-Language Models with Surgical Data: A New Dataset and Broad Benchmarking Study Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T06:01:40.799960Z

Source-reported events for the cited work

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Observation e32cb9e8-b0ef-4d66-b6cc-7b158b9400bb · inbound

Generalized Trajectory Scoring for End-to-end Multimodal Planning cites this paper.

Generalized Trajectory Scoring for End-to-end Multimodal Planning Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T05:59:20.113958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 015d056d-5c13-4196-aea6-d227d4923433 · inbound

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping cites this paper.

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T19:17:14.827230Z

Source-reported events for the cited work

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Observation eed948d9-13f3-4329-89ea-d7e0b5637b04 · inbound

Online Human Action Detection during Escorting cites this paper.

Online Human Action Detection during Escorting Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T21:40:34.849404Z

Source-reported events for the cited work

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Observation 7f796b17-4330-4239-b65f-20fa3bcc3bca · inbound

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception cites this paper.

StixelNExT++: Lightweight Monocular Scene Segmentation and Representation for Collective Perception Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T19:03:10.196940Z

Source-reported events for the cited work

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Observation 987f3ed6-fe38-47e6-8a36-81d471dafb96 · inbound

BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models? cites this paper.

BenchDepth: Are We on the Right Way to Evaluate Depth Foundation Models? Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T15:38:59.360973Z

Source-reported events for the cited work

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Observation 09df334c-cc2b-4bca-862e-2c759e2f4329 · inbound

3D Plant Root Skeleton Detection and Extraction cites this paper.

3D Plant Root Skeleton Detection and Extraction Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T21:44:58.287614Z

Source-reported events for the cited work

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Observation 6be93769-8992-4672-b72f-f9a4a8e4ffb0 · inbound

Advances and Trends in the 3D Reconstruction of the Shape and Motion of Animals cites this paper.

Advances and Trends in the 3D Reconstruction of the Shape and Motion of Animals Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T17:35:44.737792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e7c7494-16c5-4190-ac1d-e8f5f586a914 · inbound

Maybe you don't need a U-Net: convolutional feature upsampling for materials micrograph segmentation cites this paper.

Maybe you don't need a U-Net: convolutional feature upsampling for materials micrograph segmentation Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T16:44:21.085210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2bf6f08-0da7-4ba4-bf02-2d7d592c5865 · inbound

Doctoral Thesis: Geometric Deep Learning For Camera Pose Prediction, Registration, Depth Estimation, and 3D Reconstruction cites this paper.

Doctoral Thesis: Geometric Deep Learning For Camera Pose Prediction, Registration, Depth Estimation, and 3D Reconstruction Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 267

Resolution: unresolved; no resolver link, observed 2026-08-05T12:10:09.621591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b759558-6cb2-41ad-8783-5f181454ba98 · inbound

The System Description of CPS Team for Track on Driving with Language of CVPR 2024 Autonomous Grand Challenge cites this paper.

The System Description of CPS Team for Track on Driving with Language of CVPR 2024 Autonomous Grand Challenge Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T17:11:16.281726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7d370d4-f307-4cdb-94cf-855746e7c966 · inbound

Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer cites this paper.

Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T07:54:32.479332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99b395f6-4731-4cdb-a60e-b3616940b4c7 · inbound

CARI4D: Category Agnostic 4D Reconstruction of Human-Object Interaction cites this paper.

CARI4D: Category Agnostic 4D Reconstruction of Human-Object Interaction Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:38:37.566266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 78d406ad-8075-4317-bf3a-8963dcd2322a · inbound

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography cites this paper.

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:06:03.537404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eaa3d41b-681d-4846-8d7a-73e8c7476824 · inbound

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography cites this paper.

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-21T09:54:05.675501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4da39234-24fb-4440-b3b8-f1571c168189 · inbound

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography cites this paper.

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-12T21:27:21.397830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e1a7d86-22bf-415a-b957-81e7db26fca1 · inbound

PAT-VCM: Plug-and-Play Auxiliary Tokens for Video Coding for Machines cites this paper.

PAT-VCM: Plug-and-Play Auxiliary Tokens for Video Coding for Machines Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T09:56:01.865549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4a6de45-4ed5-4e17-97e1-76048193cf55 · inbound

MLG-Stereo: ViT Based Stereo Matching with Multi-Stage Local-Global Enhancement cites this paper.

MLG-Stereo: ViT Based Stereo Matching with Multi-Stage Local-Global Enhancement Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-10T00:14:46.652568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f9662716-befe-436a-ad58-71ddb1279dd3 · inbound

No Pose, No Problem in 4D: Feed-Forward Dynamic Gaussians from Unposed Multi-View Videos cites this paper.

No Pose, No Problem in 4D: Feed-Forward Dynamic Gaussians from Unposed Multi-View Videos Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:31:10.145920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b1eeb0ae-41ef-4a83-83b9-fd7764c7e13a · inbound

Sparse-LiDAR Prompting of Monocular Geometry Foundations: An Empirical Study Toward Long-Range Driving Depth cites this paper.

Sparse-LiDAR Prompting of Monocular Geometry Foundations: An Empirical Study Toward Long-Range Driving Depth Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T18:53:51.040208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8b2c0f37-cd7f-461d-9f13-5dfcc415dcb9 · inbound

VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision cites this paper.

VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:38:59.509276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 157d5b44-c7fb-4046-8b04-fb09a0e06c69 · inbound

VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision cites this paper.

VEGA: Learning Navigation VLAs from In-the-Wild Egocentric Video with Geometric Trajectory Supervision Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T11:03:52.653803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 798e482e-a7b7-4f32-83d6-5fff8b74d9ac · inbound

The Multipath Blind Spot: $K$-Agnostic Robust Calibration for Sparse-Anchor Metric Depth from Frozen Foundations cites this paper.

The Multipath Blind Spot: $K$-Agnostic Robust Calibration for Sparse-Anchor Metric Depth from Frozen Foundations Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-11T21:42:00.898441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5c17dca-52e7-4dec-aca4-81d6808f3a5c · inbound

SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion cites this paper.

SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 64

Resolution: metadata mismatch; local_arxiv, observed 2026-07-07T12:53:50.398627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4954d931-0b2d-4d5a-b0c2-453750186f1b · inbound

Geometric Collapse: When Vision Models Fail to Verify Physical Causality cites this paper.

Geometric Collapse: When Vision Models Fail to Verify Physical Causality Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T00:06:37.939399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6c7d82b-09f9-48de-8798-a770d121f49b · inbound

RoughNet: Mapping Arctic Sea Ice Roughness Using Diffusion-Based Super-Resolution of Satellite Imagery cites this paper.

RoughNet: Mapping Arctic Sea Ice Roughness Using Diffusion-Based Super-Resolution of Satellite Imagery Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T05:24:40.193836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a97d50e-b18c-40fb-811f-ff676b901c52 · inbound

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement cites this paper.

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-01T16:34:24.525121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9d972f6-6e6e-49d5-bce4-49a11413deb0 · inbound

Kitchen Robotic Manipulation utilizing Foundation Models cites this paper.

Kitchen Robotic Manipulation utilizing Foundation Models Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T00:49:13.636034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.