mlsanityData to 14 Oct 2026

DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes

arXiv 2110.11590 ↗First posted 22 Oct 2021cs.CVcited by 46

Not on the map. Why?

Abstract (arXiv)

This manual is intended to provide a detailed description of the DIML/CVL RGB-D dataset. This dataset is comprised of 2M color images and their corresponding depth maps from a great variety of natural indoor and outdoor scenes. The indoor dataset was constructed using the Microsoft Kinect v2, while the outdoor dataset was built using the stereo cameras (ZED stereo camera and built-in stereo camera). Table I summarizes the details of our dataset, including acquisition, processing, format, and toolbox. Refer to Section II and III for more details.

Key facts. Cited by 46 papers in the map (data through 14 Oct 2026). Builds on 2 of its 10 references that are in the map. First posted on arXiv 22 Oct 2021.

Builds on

2 of 10 references.

References · 2

  1. 2015A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimationcited by 881
  2. 2014Computing the Stereo Matching Cost with a Convolutional Neural Networkcited by 74

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 8; 2024: 17; 2025: 14; 2026: 7.

46 papers.

Sort:

By area:

  1. 2024Depth Anything V2cited by 1,422
  2. 2024Depth Anything: Unleashing the Power of Large-Scale Unlabeled Datacited by 1,360
  3. 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 692
  4. 2024Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimationcited by 395
  5. 2023Metric3D: Towards Zero-shot Metric 3D Prediction from A Single Imagecited by 365
  6. 2024DepthFM: Fast Monocular Depth Estimation with Flow Matchingcited by 76
  7. 2024Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimationcited by 74
  8. 2024SpatialPIN: Enhancing Spatial Reasoning Capabilities of Vision-Language Models through Prompting and Interacting 3D Priorscited by 54
  9. 2025Pixel-Perfect Depth with Semantics-Prompted Diffusion Transformerscited by 51
  10. 2024Stereo Anywhere: Robust Zero-Shot Deep Stereo Matching Even Where Either Stereo or Mono Failcited by 47
  11. 2024Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentationcited by 38
  12. 2023Zero-Shot Metric Depth with a Field-of-View Conditioned Diffusion Modelcited by 29
34 more
  1. 2025Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Modelcited by 18
  2. 2024ScaleDepth: Decomposing Metric Depth Estimation into Scale Prediction and Relative Depth Estimationcited by 15
  3. 2024DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimationcited by 13
  4. 2023The Second Monocular Depth Estimation Challengecited by 12
  5. 2025Depth Anything at Any Conditioncited by 12
  6. 2024The Third Monocular Depth Estimation Challengecited by 10
  7. 2024SPARK: Multi-Vision Sensor Perception and Reasoning Benchmark for Large-scale Vision-Language Modelscited by 9
  8. 2025The Fourth Monocular Depth Estimation Challengecited by 8
  9. 2023Advances and Challenges in Multimodal Remote Sensing Image Registrationcited by 7
  10. 2023Robust Geometry-Preserving Depth Estimation Using Differentiable Renderingcited by 6
  11. 2024PHISWID: Physics-Inspired Underwater Image Dataset Synthesized from RGB-D Imagescited by 6
  12. 2025Learning 4D Panoptic Scene Graph Generation from Rich 2D Visual Scenecited by 6
  13. 2023Knowledge Distillation for Feature Extraction in Underwater VSLAMcited by 5
  14. 2023Mobile AR Depth Estimation: Challenges & Prospects -- Extended Versioncited by 3
  15. 2024D4D: An RGBD diffusion model to boost monocular depth estimationcited by 3
  16. 2024Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarkingcited by 3
  17. 2026DeFM: Learning Foundation Representations from Depth for Roboticscited by 3
  18. 2024SM4Depth: Seamless Monocular Metric Depth Estimation across Multiple Cameras and Scenes by One Modelcited by 2
  19. 2025OSDM-MReg: Multimodal Image Registration based One Step Diffusion Modelcited by 2
  20. 2025Boosting Zero-shot Stereo Matching using Large-scale Mixed Images Sources in the Real Worldcited by 2
  21. 2025Towards Depth Foundation Model: Recent Trends in Vision-Based Depth Estimationcited by 2
  22. 2026Pixel-Perfect Visual Geometry Estimationcited by 2
  23. 2023FocDepthFormer: Transformer with latent LSTM for Depth Estimation from Focal Stackcited by 1
  24. 2025Discriminately Treating Motion Components Evolves Joint Depth and Ego-Motion Learningcited by 1
  25. 2025Multi-Order Matching Network for Alignment-Free Depth Super-Resolutioncited by 1
  26. 2026DepthART: Scaling Foundation Monocular Depth to Tiny Modelscited by 1
  27. 2024Introducing a Class-Aware Metric for Monocular Depth Estimation: An Automotive Perspectivecited by 0
  28. 2025VGLD: Visually-Guided Linguistic Disambiguation for Monocular Depth Scale Recoverycited by 0
  29. 2025Collaborative Learning for Unsupervised Multimodal Remote Sensing Image Registration: Integrating Self-Supervision and MIM-Guided Diffusion-Based Image Translationcited by 0
  30. 2025EfficientDepth: A Fast and Detail-Preserving Monocular Depth Estimation Modelcited by 0
  31. 2026Vision-Guided Outdoor Flight and Obstacle Evasion via Reinforcement Learningcited by 0
  32. 2026SpatialBench: Is Your Spatial Foundation Model an All-Round Player?cited by 0
  33. 2026Breaking the Horizontal Prior: From Long-Tailed Orientation Bias to Roll-Robust Monocular Depth Estimationcited by 0
  34. 2026RGBD20K: A Large-Scale Benchmark for RGB-D Semantic Segmentationcited by 0