mlsanityData to 14 Oct 2026

Deep Hough Voting for 3D Object Detection in Point Clouds

arXiv 1904.09664 ↗First posted 21 Apr 2019cs.CVcited by 648

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Abstract (arXiv)

Current 3D object detection methods are heavily influenced by 2D detectors. In order to leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids (i.e., to voxel grids or to bird's eye view images), or rely on detection in 2D images to propose 3D boxes. Few works have attempted to directly detect objects in point clouds. In this work, we return to first principles to construct a 3D detection pipeline for point cloud data and as generic as possible. However, due to the sparse nature of the data -- samples from 2D manifolds in 3D space -- we face a major challenge when directly predicting bounding box parameters from scene points: a 3D object centroid can be far from any surface point thus hard to regress accurately in one step. To address the challenge, we propose VoteNet, an end-to-end 3D object detection network based on a synergy of deep point set networks and Hough voting. Our model achieves state-of-the-art 3D detection on two large datasets of real 3D scans, ScanNet and SUN RGB-D with a simple design, compact model size and high efficiency. Remarkably, VoteNet outperforms previous methods by using purely geometric information without relying on color images.

Key facts. Cited by 648 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Apr 2019.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 111; 2022: 160; 2023: 148; 2024: 116; 2025: 82; 2026: 31.

648 papers.

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  1. 2021KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3Dcited by 575
  2. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 572
  3. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 466
  4. 2021ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Datacited by 454
  5. 2021ScanQA: 3D Question Answering for Spatial Scene Understandingcited by 346
  6. 2021An End-to-End Transformer Model for 3D Object Detectioncited by 329
  7. 2022SQA3D: Situated Question Answering in 3D Scenescited by 314
  8. 2022Mask3D: Mask Transformer for 3D Semantic Instance Segmentationcited by 303
  9. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
  10. 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Trackingcited by 222
  11. 2021Self-Supervised Pretraining of 3D Features on any Point-Cloudcited by 217
  12. 2021Group-Free 3D Object Detection via Transformerscited by 215
38 more
  1. 2023LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planningcited by 210
  2. 2022Unifying Voxel-based Representation with Transformer for 3D Object Detectioncited by 202
  3. 2022SoftGroup for 3D Instance Segmentation on Point Cloudscited by 200
  4. 2022CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understandingcited by 198
  5. 2021ManiSkill: Generalizable Manipulation Skill Benchmark with Large-Scale Demonstrationscited by 197
  6. 2021Spatio-temporal Self-Supervised Representation Learning for 3D Point Cloudscited by 180
  7. 2024Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoningcited by 175
  8. 2021Multimodal Virtual Point 3D Detectioncited by 166
  9. 2021SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequencescited by 163
  10. 2024Oryx MLLM: On-Demand Spatial-Temporal Understanding at Arbitrary Resolutioncited by 159
  11. 2021ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detectioncited by 157
  12. 2021Geometry Uncertainty Projection Network for Monocular 3D Object Detectioncited by 156
  13. 2022Masked Discrimination for Self-Supervised Learning on Point Cloudscited by 155
  14. 2023EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AIcited by 147
  15. 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 145
  16. 2021FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimationcited by 144
  17. 2021InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referringcited by 141
  18. 2022Multimodal Token Fusion for Vision Transformerscited by 136
  19. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  20. 2022Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Cloudscited by 131
  21. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  22. 2023Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenescited by 129
  23. 2021Bottom Up Top Down Detection Transformers for Language Grounding in Images and Point Cloudscited by 128
  24. 2021SAT: 2D Semantics Assisted Training for 3D Visual Groundingcited by 124
  25. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  26. 2022Language Conditioned Spatial Relation Reasoning for 3D Object Groundingcited by 122
  27. 2022Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?cited by 122
  28. 2023DSVT: Dynamic Sparse Voxel Transformer with Rotated Setscited by 122
  29. 2021RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detectioncited by 115
  30. 20223D-SPS: Single-Stage 3D Visual Grounding via Referred Point Progressive Selectioncited by 110
  31. 2023OctFormer: Octree-based Transformers for 3D Point Cloudscited by 109
  32. 2025GPT4Scene: Understand 3D Scenes from Videos with Vision-Language Modelscited by 109
  33. 2021Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentationcited by 107
  34. 2021TransformerFusion: Monocular RGB Scene Reconstruction using Transformerscited by 106
  35. 2021Fast Point Transformercited by 104
  36. 2021DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistencycited by 103
  37. 2022Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Cloudscited by 102
  38. 2022EDA: Explicit Text-Decoupling and Dense Alignment for 3D Visual Groundingcited by 99

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