mlsanityData to 7 Oct 2026

Depth Anything V2

arXiv 2406.09414 ↗First posted 13 Jun 2024cs.CVcited by 1,385

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Cited by 133 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

This work presents Depth Anything V2. Without pursuing fancy techniques, we aim to reveal crucial findings to pave the way towards building a powerful monocular depth estimation model. Notably, compared with V1, this version produces much finer and more robust depth predictions through three key practices: 1) replacing all labeled real images with synthetic images, 2) scaling up the capacity of our teacher model, and 3) teaching student models via the bridge of large-scale pseudo-labeled real images. Compared with the latest models built on Stable Diffusion, our models are significantly more efficient (more than 10x faster) and more accurate. We offer models of different scales (ranging from 25M to 1.3B params) to support extensive scenarios. Benefiting from their strong generalization capability, we fine-tune them with metric depth labels to obtain our metric depth models. In addition to our models, considering the limited diversity and frequent noise in current test sets, we construct a versatile evaluation benchmark with precise annotations and diverse scenes to facilitate future research.

Key facts. Cited by 1,385 papers in the map (data through 7 Oct 2026). Builds on 85 of its 103 references that are in the map. First posted on arXiv 13 Jun 2024.

Builds on

85 of 103 references.

References · 85

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  5. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  6. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  7. 2023Segment Anythingcited by 8,158
  8. 2023Visual Instruction Tuningcited by 7,792
  9. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
  10. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  11. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  12. 2022A ConvNet for the 2020scited by 3,545
38 more
  1. 2015Domain-Adversarial Training of Neural Networkscited by 3,023
  2. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  3. 2021BEiT: BERT Pre-Training of Image Transformerscited by 2,360
  4. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  5. 2020FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidencecited by 2,080
  6. 2014Unsupervised Domain Adaptation by Backpropagationcited by 1,906
  7. 2021Vision Transformers for Dense Predictioncited by 1,789
  8. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  9. 2015LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loopcited by 1,350
  10. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  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. 2016Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfercited by 1,059
  16. 2019Unsupervised Data Augmentation for Consistency Trainingcited by 1,057
  17. 2021Segmenter: Transformer for Semantic Segmentationcited by 855
  18. 2023Vision Transformers Need Registerscited by 844
  19. 2016Playing for Data: Ground Truth from Computer Gamescited by 816
  20. 2018MegaDepth: Learning Single-View Depth Prediction from Internet Photoscited by 731
  21. 2018Deep Ordinal Regression Network for Monocular Depth Estimationcited by 721
  22. 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 646
  23. 2020AdaBins: Depth Estimation using Adaptive Binscited by 596
  24. 2020Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understandingcited by 593
  25. 2019Improved Knowledge Distillation via Teacher Assistantcited by 567
  26. 2022Vision Transformer Adapter for Dense Predictionscited by 564
  27. 2024BLINK: Multimodal Large Language Models Can See but Not Perceivecited by 529
  28. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 517
  29. 2020TartanAir: A Dataset to Push the Limits of Visual SLAMcited by 494
  30. 2019BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networkscited by 487
  31. 2022InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutionscited by 479
  32. 2013Do Deep Nets Really Need to be Deep?cited by 466
  33. 2018Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Drivingcited by 455
  34. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 389
  35. 2024UniDepth: Universal Monocular Metric Depth Estimationcited by 375
  36. 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 357
  37. 2020Virtual KITTI 2cited by 345
  38. 2022OneFormer: One Transformer to Rule Universal Image Segmentationcited by 327

50 most cited of 85 All 85 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 141; 2025: 637; 2026: 607.

1,385 papers.

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  1. 2025VGGT: Visual Geometry Grounded Transformercited by 1,475
  2. 2025Qwen-Image Technical Reportcited by 973
  3. 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 626
  4. 2024MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motioncited by 431
  5. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 395
  6. 2025GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Controlcited by 325
  7. 2025MapAnything: Universal Feed-Forward Metric 3D Reconstructioncited by 295
  8. 2025π3: Permutation-Equivariant Visual Geometry Learningcited by 292
  9. 2024MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervisioncited by 290
  10. 2024DepthSplat: Connecting Gaussian Splatting and Depthcited by 275
  11. 2025MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Detailscited by 250
  12. 2024MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videoscited by 224
38 more
  1. 2025DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledgecited by 203
  2. 2024DepthCrafter: Generating Consistent Long Depth Sequences for Open-world Videoscited by 202
  3. 2025Video Depth Anything: Consistent Depth Estimation for Super-Long Videoscited by 202
  4. 2025UniDepthV2: Universal Monocular Metric Depth Estimation Made Simplercited by 170
  5. 2025FoundationStereo: Zero-Shot Stereo Matchingcited by 168
  6. 2024Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Predictioncited by 163
  7. 2025ViPE: Video Pose Engine for 3D Geometric Perceptioncited by 162
  8. 2025PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understandingcited by 147
  9. 2024HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videoscited by 122
  10. 2025TrajectoryCrafter: Redirecting Camera Trajectory for Monocular Videos via Diffusion Modelscited by 120
  11. 2025Sonata: Self-Supervised Learning of Reliable Point Representationscited by 108
  12. 2024UniReal: Universal Image Generation and Editing via Learning Real-world Dynamicscited by 100
  13. 2025Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Controlcited by 95
  14. 2024Stereo4D: Learning How Things Move in 3D from Internet Stereo Videoscited by 89
  15. 2025DexGraspVLA: A Vision-Language-Action Framework Towards General Dexterous Graspingcited by 87
  16. 2025Visual Spatial Tuningcited by 85
  17. 2025SpatialTrackerV2: 3D Point Tracking Made Easycited by 84
  18. 2024Fine-Tuning Image-Conditional Diffusion Models is Easier than You Thinkcited by 82
  19. 2024Align3R: Aligned Monocular Depth Estimation for Dynamic Videoscited by 79
  20. 2025Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysiscited by 78
  21. 2024GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Controlcited by 76
  22. 2025STream3R: Scalable Sequential 3D Reconstruction with Causal Transformercited by 76
  23. 2025RayZer: A Self-supervised Large View Synthesis Modelcited by 74
  24. 2024Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimationcited by 73
  25. 2025SpatialVID: A Large-Scale Video Dataset with Spatial Annotationscited by 72
  26. 2024Perception Tokens Enhance Visual Reasoning in Multimodal Language Modelscited by 68
  27. 2026WorldArena: A Unified Benchmark for Evaluating Perception and Functional Utility of Embodied World Modelscited by 68
  28. 2025Geo4D: Leveraging Video Generators for Geometric 4D Scene Reconstructioncited by 66
  29. 2025SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoningcited by 65
  30. 20253D and 4D World Modeling: A Surveycited by 64
  31. 2025UniK3D: Universal Camera Monocular 3D Estimationcited by 60
  32. 2024A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trendscited by 58
  33. 2024Depth Any Video with Scalable Synthetic Datacited by 57
  34. 2024IGEV++: Iterative Multi-range Geometry Encoding Volumes for Stereo Matchingcited by 55
  35. 2025RealCam-I2V: Real-World Image-to-Video Generation with Interactive Complex Camera Controlcited by 54
  36. 2024UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentationcited by 53
  37. 2024InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Modelscited by 53
  38. 2025EditVerse: Unifying Image and Video Editing and Generation with In-Context Learningcited by 53

50 most cited of 1,385 All 1,385 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2024Diffusion Models for Monocular Depth Estimation: Overcoming Challenging Conditions
  2. 2024DepthART: Monocular Depth Estimation as Autoregressive Refinement Task
  3. 2024Iris: Integrating Language into Diffusion-based Monocular Depth Estimation
  4. 2023Monocular Depth Estimation using Diffusion Models
  5. 2026Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation
  6. 2025Zero-shot Depth Completion via Test-time Alignment with Affine-invariant Depth Prior
  7. 2024GRIN: Zero-Shot Metric Depth with Pixel-Level Diffusion
  8. 2024Unsupervised Monocular Depth Estimation Based on Hierarchical Feature-Guided Diffusion