mlsanityData to 14 Oct 2026

Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture

arXiv 1411.4734 ↗First posted 18 Nov 2014cs.CVcited by 483

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Cited by 20 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper we address three different computer vision tasks using a single basic architecture: depth prediction, surface normal estimation, and semantic labeling. We use a multiscale convolutional network that is able to adapt easily to each task using only small modifications, regressing from the input image to the output map directly. Our method progressively refines predictions using a sequence of scales, and captures many image details without any superpixels or low-level segmentation. We achieve state-of-the-art performance on benchmarks for all three tasks.

Key facts. Cited by 483 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Nov 2014.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 127; 2022: 102; 2023: 86; 2024: 89; 2025: 49; 2026: 30.

483 papers.

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  1. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 470
  2. 2021In-Place Scene Labelling and Understanding with Implicit Scene Representationcited by 415
  3. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 404
  4. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 395
  5. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 327
  6. 2023SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Drivingcited by 316
  7. 2022MultiMAE: Multi-modal Multi-task Masked Autoencoderscited by 291
  8. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 286
  9. 2024Sapiens: Foundation for Human Vision Modelscited by 229
  10. 2023Affordances from Human Videos as a Versatile Representation for Roboticscited by 226
  11. 2022Omnivore: A Single Model for Many Visual Modalitiescited by 215
  12. 2021The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depthcited by 190
38 more
  1. 2024StableNormal: Reducing Diffusion Variance for Stable and Sharp Normalcited by 154
  2. 2023SelfOcc: Self-Supervised Vision-Based 3D Occupancy Predictioncited by 133
  3. 2021Transformer-Based Attention Networks for Continuous Pixel-Wise Predictioncited by 125
  4. 2024Rethinking Inductive Biases for Surface Normal Estimationcited by 124
  5. 20234M: Massively Multimodal Masked Modelingcited by 120
  6. 2021Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimationcited by 116
  7. 2023The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimationcited by 116
  8. 2022P3Depth: Monocular Depth Estimation with a Piecewise Planarity Priorcited by 107
  9. 2022Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimationcited by 100
  10. 2025Hi3DGen: High-fidelity 3D Geometry Generation from Images via Normal Bridgingcited by 99
  11. 2021Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Predictioncited by 90
  12. 2022BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereocited by 90
  13. 2023Monocular Depth Estimation using Diffusion Modelscited by 87
  14. 2024Fine-Tuning Image-Conditional Diffusion Models is Easier than You Thinkcited by 83
  15. 2023DiffusionDepth: Diffusion Denoising Approach for Monocular Depth Estimationcited by 82
  16. 2021Endo-Depth-and-Motion: Reconstruction and Tracking in Endoscopic Videos using Depth Networks and Photometric Constraintscited by 81
  17. 2022Learning-based Inverse Rendering of Complex Indoor Scenes with Differentiable Monte Carlo Raytracingcited by 78
  18. 2025Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysiscited by 78
  19. 2021ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentationcited by 77
  20. 2024Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimationcited by 74
  21. 2021Unsupervised Scale-consistent Depth Learning from Videocited by 69
  22. 2021Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimationcited by 63
  23. 2022IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenescited by 62
  24. 2021OperA: Attention-Regularized Transformers for Surgical Phase Recognitioncited by 60
  25. 2021PolyViT: Co-training Vision Transformers on Images, Videos and Audiocited by 58
  26. 2021OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous Drivingcited by 57
  27. 2024InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Priorcited by 56
  28. 2021SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representationscited by 55
  29. 2023AG3D: Learning to Generate 3D Avatars from 2D Image Collectionscited by 55
  30. 2024AffordanceLLM: Grounding Affordance from Vision Language Modelscited by 55
  31. 2021Shape from Polarization for Complex Scenes in the Wildcited by 53
  32. 2022SC-DepthV3: Robust Self-supervised Monocular Depth Estimation for Dynamic Scenescited by 52
  33. 20244M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalitiescited by 52
  34. 2025Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformerscited by 51
  35. 2021Virtual Normal: Enforcing Geometric Constraints for Accurate and Robust Depth Predictioncited by 48
  36. 20213D-to-2D Distillation for Indoor Scene Parsingcited by 48
  37. 2021Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimationcited by 48
  38. 2022Disentangling Object Motion and Occlusion for Unsupervised Multi-frame Monocular Depthcited by 48

50 most cited of 483 All 483 (JSON)