mlsanityData to 7 Oct 2026

Evaluation of CNN-based Single-Image Depth Estimation Methods

arXiv 1805.01328 ↗First posted 3 May 2018cs.CVcited by 137

Not on the map. Why?

Cited by 24 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set of novel quality criteria, allowing for a more detailed analysis by focusing on specific characteristics of depth maps. In particular, we address the preservation of edges and planar regions, depth consistency, and absolute distance accuracy. In order to employ these metrics to evaluate and compare state-of-the-art single-image depth estimation approaches, we provide a new high-quality RGB-D dataset. We used a DSLR camera together with a laser scanner to acquire high-resolution images and highly accurate depth maps. Experimental results show the validity of our proposed evaluation protocol.

Key facts. Cited by 137 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 May 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 13; 2023: 10; 2024: 33; 2025: 31; 2026: 36.

137 papers.

Sort:

By area:

  1. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,346
  2. 2023ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depthcited by 646
  3. 2024Depth Pro: Sharp Monocular Metric Depth in Less Than a Secondcited by 395
  4. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 389
  5. 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 357
  6. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 283
  7. 2025MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Detailscited by 250
  8. 2024Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Predictioncited by 163
  9. 2024StableNormal: Reducing Diffusion Variance for Stable and Sharp Normalcited by 153
  10. 2021MINE: Towards Continuous Depth MPI with NeRF for Novel View Synthesiscited by 133
  11. 2024Rethinking Inductive Biases for Surface Normal Estimationcited by 122
  12. 2021Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Mergingcited by 104
38 more
  1. 2022LocalBins: Improving Depth Estimation by Learning Local Distributionscited by 92
  2. 2024Fine-Tuning Image-Conditional Diffusion Models is Easier than You Thinkcited by 82
  3. 2025Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysiscited by 78
  4. 2025WorldMirror: Universal 3D World Reconstruction with Any-Prior Promptingcited by 60
  5. 2022Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepthcited by 58
  6. 2022Hierarchical Normalization for Robust Monocular Depth Estimationcited by 51
  7. 2024Marigold-DC: Zero-Shot Monocular Depth Completion with Guided Diffusioncited by 47
  8. 2024ECoDepth: Effective Conditioning of Diffusion Models for Monocular Depth Estimationcited by 45
  9. 2022Towards Accurate Reconstruction of 3D Scene Shape from A Single Monocular Imagecited by 42
  10. 2026Image Generators are Generalist Vision Learnerscited by 40
  11. 2021Pano3D: A Holistic Benchmark and a Solid Baseline for 360o Depth Estimationcited by 37
  12. 2021StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimationcited by 36
  13. 2025LBM: Latent Bridge Matching for Fast Image-to-Image Translationcited by 36
  14. 2021Single Image Depth Prediction with Wavelet Decompositioncited by 34
  15. 2026HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worldscited by 34
  16. 2025Detect Anything 3D in the Wildcited by 32
  17. 2022IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertaintycited by 30
  18. 2025DepthLM: Metric Depth From Vision Language Modelscited by 29
  19. 2024BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimationcited by 28
  20. 2024OMNI-DC: Highly Robust Depth Completion with Multiresolution Depth Integrationcited by 28
  21. 2025NormalCrafter: Learning Temporally Consistent Normals from Video Diffusion Priorscited by 25
  22. 2024SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillationcited by 21
  23. 2025From Editor to Dense Geometry Estimatorcited by 20
  24. 2022From 2D to 3D: Re-thinking Benchmarking of Monocular Depth Predictioncited by 19
  25. 2025MoRE: 3D Visual Geometry Reconstruction Meets Mixture-of-Expertscited by 19
  26. 2022Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Mattercited by 18
  27. 2025Orchid: Image Latent Diffusion for Joint Appearance and Geometry Generationcited by 17
  28. 2025Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Modelcited by 16
  29. 2024PatchRefiner: Leveraging Synthetic Data for Real-Domain High-Resolution Monocular Metric Depth Estimationcited by 15
  30. 2024ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimationcited by 15
  31. 2022The Monocular Depth Estimation Challengecited by 13
  32. 2023The Second Monocular Depth Estimation Challengecited by 12
  33. 2023G2-MonoDepth: A General Framework of Generalized Depth Inference from Monocular RGB+X Datacited by 12
  34. 2022A Survey on RGB-D Datasetscited by 11
  35. 2021Dimensions of Motion: Monocular Prediction through Flow Subspacescited by 10
  36. 2024The Third Monocular Depth Estimation Challengecited by 10
  37. 2026MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sourcescited by 10
  38. 2021Machine-learned 3D Building Vectorization from Satellite Imagerycited by 9

50 most cited of 137 All 137 (JSON)