mlsanityData to 7 Oct 2026

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

arXiv 2401.10891 ↗First posted 19 Jan 2024cs.CVcited by 1,346

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Cited by 128 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This work presents Depth Anything, a highly practical solution for robust monocular depth estimation. Without pursuing novel technical modules, we aim to build a simple yet powerful foundation model dealing with any images under any circumstances. To this end, we scale up the dataset by designing a data engine to collect and automatically annotate large-scale unlabeled data (~62M), which significantly enlarges the data coverage and thus is able to reduce the generalization error. We investigate two simple yet effective strategies that make data scaling-up promising. First, a more challenging optimization target is created by leveraging data augmentation tools. It compels the model to actively seek extra visual knowledge and acquire robust representations. Second, an auxiliary supervision is developed to enforce the model to inherit rich semantic priors from pre-trained encoders. We evaluate its zero-shot capabilities extensively, including six public datasets and randomly captured photos. It demonstrates impressive generalization ability. Further, through fine-tuning it with metric depth information from NYUv2 and KITTI, new SOTAs are set. Our better depth model also results in a better depth-conditioned ControlNet. Our models are released at https://github.com/LiheYoung/Depth-Anything.

Key facts. Cited by 1,346 papers in the map (data through 7 Oct 2026). Builds on 67 of its 89 references that are in the map. First posted on arXiv 19 Jan 2024.

Builds on

67 of 89 references.

References · 67

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  6. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  7. 2023Segment Anythingcited by 8,158
  8. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
  9. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  10. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,712
  11. 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
  12. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
38 more
  1. 2022A ConvNet for the 2020scited by 3,545
  2. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
  3. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  4. 2019CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Featurescited by 2,875
  5. 2021BEiT: BERT Pre-Training of Image Transformerscited by 2,360
  6. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  7. 2020FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidencecited by 2,080
  8. 2021Vision Transformers for Dense Predictioncited by 1,789
  9. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  10. 2015LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loopcited by 1,350
  11. 2018BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learningcited by 1,282
  12. 2018Unified Perceptual Parsing for Scene Understandingcited by 1,265
  13. 2014Depth Map Prediction from a Single Image using a Multi-Scale Deep Networkcited by 1,264
  14. 2021Swin Transformer V2: Scaling Up Capacity and Resolutioncited by 1,215
  15. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  16. 2018MegaDepth: Learning Single-View Depth Prediction from Internet Photoscited by 731
  17. 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 646
  18. 2020AdaBins: Depth Estimation using Adaptive Binscited by 596
  19. 2020Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understandingcited by 593
  20. 2022Vision Transformer Adapter for Dense Predictionscited by 564
  21. 2020TartanAir: A Dataset to Push the Limits of Visual SLAMcited by 494
  22. 2019BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networkscited by 487
  23. 2018Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Drivingcited by 455
  24. 20193D Packing for Self-Supervised Monocular Depth Estimationcited by 437
  25. 2023Segment Anything in High Qualitycited by 373
  26. 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 357
  27. 2020Rethinking Pre-training and Self-trainingcited by 352
  28. 2022OneFormer: One Transformer to Rule Universal Image Segmentationcited by 327
  29. 2021End-to-End Semi-Supervised Object Detection with Soft Teachercited by 315
  30. 2020Google Landmarks Dataset v2 -- A Large-Scale Benchmark for Instance-Level Recognition and Retrievalcited by 305
  31. 2023Recognize Anything: A Strong Image Tagging Modelcited by 305
  32. 2023Unleashing Text-to-Image Diffusion Models for Visual Perceptioncited by 266
  33. 2019DIODE: A Dense Indoor and Outdoor DEpth Datasetcited by 236
  34. 2019Enforcing geometric constraints of virtual normal for depth predictioncited by 233
  35. 2019Billion-scale semi-supervised learning for image classificationcited by 232
  36. 2019Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Drivingcited by 188
  37. 2021ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentationcited by 184
  38. 2016Single-Image Depth Perception in the Wildcited by 179

50 most cited of 67 All 67 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 371; 2025: 584; 2026: 391.

1,346 papers.

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  1. 2025VGGT: Visual Geometry Grounded Transformercited by 1,475
  2. 2024Depth Anything V2cited by 1,385
  3. 2025Qwen-Image Technical Reportcited by 973
  4. 2024BLINK: Multimodal Large Language Models Can See but Not Perceivecited by 529
  5. 2025Continuous 3D Perception Model with Persistent Statecited by 527
  6. 2024MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motioncited by 431
  7. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 395
  8. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 389
  9. 2025Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Passcited by 356
  10. 2025GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Controlcited by 325
  11. 2024SpatialRGPT: Grounded Spatial Reasoning in Vision Language Modelscited by 297
  12. 2024MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervisioncited by 290
38 more
  1. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 283
  2. 2024DepthSplat: Connecting Gaussian Splatting and Depthcited by 275
  3. 2024Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Modelscited by 260
  4. 2025MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Detailscited by 250
  5. 2024Shape of Motion: 4D Reconstruction from a Single Videocited by 247
  6. 2024Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillationcited by 244
  7. 2025SAM 3D: 3Dfy Anything in Imagescited by 230
  8. 2024Sapiens: Foundation for Human Vision Modelscited by 229
  9. 2024MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videoscited by 224
  10. 2025DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledgecited by 203
  11. 2024DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videoscited by 202
  12. 2025Video Depth Anything: Consistent Depth Estimation for Super-Long Videoscited by 202
  13. 2024MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priorscited by 198
  14. 2024MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffoldscited by 177
  15. 2024T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generationcited by 177
  16. 2025FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Viewscited by 176
  17. 2025UniDepthV2: Universal Monocular Metric Depth Estimation Made Simplercited by 170
  18. 2025FoundationStereo: Zero-Shot Stereo Matchingcited by 168
  19. 2024Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Predictioncited by 163
  20. 2024CAT4D: Create Anything in 4D with Multi-View Video Diffusion Modelscited by 160
  21. 2024Lumina-mGPT: Illuminate Flexible Photorealistic Text-to-Image Generation with Multimodal Generative Pretrainingcited by 148
  22. 2024SpatialBot: Precise Spatial Understanding with Vision Language Modelscited by 146
  23. 2025WorldScore: A Unified Evaluation Benchmark for World Generationcited by 143
  24. 2024DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshingcited by 136
  25. 2024Flash3D: Feed-Forward Generalisable 3D Scene Reconstruction from a Single Imagecited by 113
  26. 2024Long-LRM: Long-sequence Large Reconstruction Model for Wide-coverage Gaussian Splatscited by 111
  27. 2024RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusioncited by 109
  28. 2025Sonata: Self-Supervised Learning of Reliable Point Representationscited by 108
  29. 2024TRAM: Global Trajectory and Motion of 3D Humans from in-the-wild Videoscited by 105
  30. 2026V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learningcited by 104
  31. 2025HD-EPIC: A Highly-Detailed Egocentric Video Datasetcited by 101
  32. 2025CAST: Component-Aligned 3D Scene Reconstruction from an RGB Imagecited by 101
  33. 2024Learning Temporally Consistent Video Depth from Video Diffusion Priorscited by 100
  34. 2024Dynamic Gaussian Marbles for Novel View Synthesis of Casual Monocular Videoscited by 96
  35. 2025Aether: Geometric-Aware Unified World Modelingcited by 94
  36. 2025Cameras as Relative Positional Encodingcited by 94
  37. 2024ImageFolder: Autoregressive Image Generation with Folded Tokenscited by 93
  38. 2025DriveSuprim: Towards Precise Trajectory Selection for End-to-End Planningcited by 91

50 most cited of 1,346 All 1,346 (JSON)