mlsanityData to 7 Oct 2026

Joint 2D-3D-Semantic Data for Indoor Scene Understanding

arXiv 1702.01105 ↗First posted 3 Feb 2017cs.CV cs.ROcited by 404

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Abstract (arXiv)

We present a dataset of large-scale indoor spaces that provides a variety of mutually registered modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. The dataset covers over 6,000m2 and contains over 70,000 RGB images, along with the corresponding depths, surface normals, semantic annotations, global XYZ images (all in forms of both regular and 360deg equirectangular images) as well as camera information. It also includes registered raw and semantically annotated 3D meshes and point clouds. The dataset enables development of joint and cross-modal learning models and potentially unsupervised approaches utilizing the regularities present in large-scale indoor spaces. The dataset is available here: http://3Dsemantics.stanford.edu/

Key facts. Cited by 404 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Feb 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 88; 2022: 79; 2023: 74; 2024: 62; 2025: 54; 2026: 47.

404 papers.

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  1. 2021Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AIcited by 579
  2. 2022OpenScene: 3D Scene Understanding with Open Vocabulariescited by 556
  3. 2021Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scanscited by 336
  4. 2023Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Drivingcited by 325
  5. 2021PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformerscited by 284
  6. 2021A Survey of Embodied AI: From Simulators to Research Taskscited by 256
  7. 2022CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformerscited by 229
  8. 2021Self-Supervised Pretraining of 3D Features on any Point-Cloudcited by 217
  9. 2024SpatialBot: Precise Spatial Understanding with Vision Language Modelscited by 146
  10. 2023Weakly Supervised 3D Open-vocabulary Segmentationcited by 133
  11. 2024Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generationcited by 129
  12. 2023Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidancecited by 123
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  1. 2021MSeg: A Composite Dataset for Multi-domain Semantic Segmentationcited by 122
  2. 2021Capturing, Reconstructing, and Simulating: the UrbanScene3D Datasetcited by 117
  3. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 114
  4. 2023FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugincited by 101
  5. 2022PanoFormer: Panorama Transformer for Indoor 360 Depth Estimationcited by 94
  6. 2021UniFuse: Unidirectional Fusion for 360circ Panorama Depth Estimationcited by 91
  7. 2021One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentationcited by 89
  8. 2023CLIP goes 3D: Leveraging Prompt Tuning for Language Grounded 3D Recognitioncited by 77
  9. 2021Learning to Stylize Novel Viewscited by 76
  10. 2021ShapeConv: Shape-aware Convolutional Layer for Indoor RGB-D Semantic Segmentationcited by 75
  11. 2022Perspective Fields for Single Image Camera Calibrationcited by 75
  12. 20213D Semantic Scene Completion: a Surveycited by 74
  13. 2024A Survey of Multimodal Large Language Model from A Data-centric Perspectivecited by 73
  14. 2021Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusioncited by 71
  15. 2022Bending Reality: Distortion-aware Transformers for Adapting to Panoramic Semantic Segmentationcited by 71
  16. 2024OpenNeRF: Open Set 3D Neural Scene Segmentation with Pixel-Wise Features and Rendered Novel Viewscited by 68
  17. 2023AdaPoinTr: Diverse Point Cloud Completion with Adaptive Geometry-Aware Transformerscited by 65
  18. 2021SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Cloudscited by 64
  19. 2022When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learningcited by 64
  20. 2021360MonoDepth: High-Resolution 360deg Monocular Depth Estimationcited by 60
  21. 2022OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusioncited by 60
  22. 2025UniK3D: Universal Camera Monocular 3D Estimationcited by 60
  23. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  24. 2022Contrastive Boundary Learning for Point Cloud Segmentationcited by 56
  25. 2023PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigmcited by 56
  26. 2022TransCG: A Large-Scale Real-World Dataset for Transparent Object Depth Completion and a Grasping Baselinecited by 55
  27. 20214DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understandingcited by 54
  28. 2022STPLS3D: A Large-Scale Synthetic and Real Aerial Photogrammetry 3D Point Cloud Datasetcited by 52
  29. 2023ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolutioncited by 52
  30. 2021Learning Semantic Segmentation of Large-Scale Point Clouds with Random Samplingcited by 51
  31. 2024GeoCalib: Learning Single-image Calibration with Geometric Optimizationcited by 50
  32. 2022SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Cloudscited by 49
  33. 20213D-to-2D Distillation for Indoor Scene Parsingcited by 47
  34. 2022Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentationcited by 46
  35. 2021Self-supervised Monocular Depth Estimation for All Day Images using Domain Separationcited by 44
  36. 2021PatchFormer: An Efficient Point Transformer with Patch Attentioncited by 43
  37. 2021LED2-Net: Monocular 360 Layout Estimation via Differentiable Depth Renderingcited by 42
  38. 2021PVT: Point-Voxel Transformer for Point Cloud Learningcited by 42

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