mlsanityData to 7 Oct 2026

Learning to Recover 3D Scene Shape from a Single Image

arXiv 2012.09365 ↗First posted 17 Dec 2020cs.CVcited by 214

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Cited by 37 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due to an unknown depth shift induced by shift-invariant reconstruction losses used in mixed-data depth prediction training, and possible unknown camera focal length. We investigate this problem in detail, and propose a two-stage framework that first predicts depth up to an unknown scale and shift from a single monocular image, and then use 3D point cloud encoders to predict the missing depth shift and focal length that allow us to recover a realistic 3D scene shape. In addition, we propose an image-level normalized regression loss and a normal-based geometry loss to enhance depth prediction models trained on mixed datasets. We test our depth model on nine unseen datasets and achieve state-of-the-art performance on zero-shot dataset generalization. Code is available at: https://git.io/Depth

Key facts. Cited by 214 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Dec 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 32; 2023: 45; 2024: 49; 2025: 46; 2026: 28.

214 papers.

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  1. 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,526
  2. 2024Depth Anything V2cited by 1,385
  3. 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 646
  4. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 467
  5. 2024MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motioncited by 431
  6. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 395
  7. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 389
  8. 2024UniDepth: Universal Monocular Metric Depth Estimationcited by 375
  9. 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 357
  10. 2023Repurposing Diffusion-Based Image Generators for Monocular Depth Estimationcited by 323
  11. 2024MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervisioncited by 290
  12. 2022MultiMAE: Multi-modal Multi-task Masked Autoencoderscited by 287
38 more
  1. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 283
  2. 2025MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Detailscited by 250
  3. 2024MegaSaM: Accurate, Fast, and Robust Structure and Motion from Casual Dynamic Videoscited by 224
  4. 2025UniDepthV2: Universal Monocular Metric Depth Estimation Made Simplercited by 170
  5. 2022SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Imagecited by 165
  6. 2024Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Predictioncited by 163
  7. 2022NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360deg Viewscited by 148
  8. 2023Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fieldscited by 122
  9. 2021Capturing, Reconstructing, and Simulating: the UrbanScene3D Datasetcited by 117
  10. 2022P3Depth: Monocular Depth Estimation with a Piecewise Planarity Priorcited by 106
  11. 2024Learning Temporally Consistent Video Depth from Video Diffusion Priorscited by 100
  12. 2024Stereo4D: Learning How Things Move in 3D from Internet Stereo Videoscited by 89
  13. 2022SimpleRecon: 3D Reconstruction Without 3D Convolutionscited by 83
  14. 2024Fine-Tuning Image-Conditional Diffusion Models is Easier than You Thinkcited by 82
  15. 2025Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysiscited by 78
  16. 2024DepthFM: Fast Monocular Depth Estimation with Flow Matchingcited by 76
  17. 2024What Matters When Repurposing Diffusion Models for General Dense Perception Tasks?cited by 74
  18. 2024Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimationcited by 73
  19. 2021Unsupervised Scale-consistent Depth Learning from Videocited by 69
  20. 2025Pow3R: Empowering Unconstrained 3D Reconstruction with Camera and Scene Priorscited by 69
  21. 2021360MonoDepth: High-Resolution 360deg Monocular Depth Estimationcited by 60
  22. 2024Depth Any Video with Scalable Synthetic Datacited by 57
  23. 2024AffordanceLLM: Grounding Affordance from Vision Language Modelscited by 55
  24. 2022Hierarchical Normalization for Robust Monocular Depth Estimationcited by 51
  25. 2022SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenescited by 50
  26. 2021Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Predictioncited by 48
  27. 2025Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformerscited by 47
  28. 20213D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Imagecited by 45
  29. 2021Toward Practical Monocular Indoor Depth Estimationcited by 42
  30. 2023HandRefiner: Refining Malformed Hands in Generated Images by Diffusion-based Conditional Inpaintingcited by 42
  31. 2024One Diffusion to Generate Them Allcited by 41
  32. 2021Planar Surface Reconstruction from Sparse Viewscited by 40
  33. 2025Matrix3D: Large Photogrammetry Model All-in-Onecited by 39
  34. 2022Achieving Risk Control in Online Learning Settingscited by 38
  35. 2025DICEPTION: A Generalist Diffusion Model for Visual Perceptual Taskscited by 37
  36. 2021StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimationcited by 36
  37. 2025LBM: Latent Bridge Matching for Fast Image-to-Image Translationcited by 36
  38. 2025GeometryCrafter: Consistent Geometry Estimation for Open-world Videos with Diffusion Priorscited by 36

50 most cited of 214 All 214 (JSON)