mlsanityData to 7 Oct 2026

VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

arXiv 1711.06396 ↗First posted 17 Nov 2017cs.CVcited by 1,323

Not on the map. Why?

Cited by 37 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality. To interface a highly sparse LiDAR point cloud with a region proposal network (RPN), most existing efforts have focused on hand-crafted feature representations, for example, a bird's eye view projection. In this work, we remove the need of manual feature engineering for 3D point clouds and propose VoxelNet, a generic 3D detection network that unifies feature extraction and bounding box prediction into a single stage, end-to-end trainable deep network. Specifically, VoxelNet divides a point cloud into equally spaced 3D voxels and transforms a group of points within each voxel into a unified feature representation through the newly introduced voxel feature encoding (VFE) layer. In this way, the point cloud is encoded as a descriptive volumetric representation, which is then connected to a RPN to generate detections. Experiments on the KITTI car detection benchmark show that VoxelNet outperforms the state-of-the-art LiDAR based 3D detection methods by a large margin. Furthermore, our network learns an effective discriminative representation of objects with various geometries, leading to encouraging results in 3D detection of pedestrians and cyclists, based on only LiDAR.

Key facts. Cited by 1,323 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Nov 2017.

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Citing papers per year: 2021: 210; 2022: 292; 2023: 293; 2024: 243; 2025: 187; 2026: 98.

1,323 papers.

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  1. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  2. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
  3. 2021BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-Viewcited by 711
  4. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
  5. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 464
  6. 2021FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detectioncited by 444
  7. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 404
  8. 2022BEVFusion: A Simple and Robust LiDAR-Camera Fusion Frameworkcited by 334
  9. 2021An End-to-End Transformer Model for 3D Object Detectioncited by 329
  10. 2023Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Drivingcited by 325
  11. 2022V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformercited by 320
  12. 2021OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communicationcited by 304
38 more
  1. 2021PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformerscited by 284
  2. 2023NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenariocited by 258
  3. 2021Voxel Transformer for 3D Object Detectioncited by 247
  4. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
  5. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  6. 2022DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detectioncited by 224
  7. 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Trackingcited by 221
  8. 2021One Million Scenes for Autonomous Driving: ONCE Datasetcited by 218
  9. 2023OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perceptioncited by 218
  10. 2021Self-Supervised Pretraining of 3D Features on any Point-Cloudcited by 217
  11. 2021Group-Free 3D Object Detection via Transformerscited by 215
  12. 2021Learning Distilled Collaboration Graph for Multi-Agent Perceptioncited by 194
  13. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  14. 2021Embracing Single Stride 3D Object Detector with Sparse Transformercited by 193
  15. 2021Probabilistic and Geometric Depth: Detecting Objects in Perspectivecited by 190
  16. 2021PandaSet: Advanced Sensor Suite Dataset for Autonomous Drivingcited by 186
  17. 2024Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AIcited by 175
  18. 2021RPVNet: A Deep and Efficient Range-Point-Voxel Fusion Network for LiDAR Point Cloud Segmentationcited by 173
  19. 2023Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Drivingcited by 168
  20. 2021Multimodal Virtual Point 3D Detectioncited by 166
  21. 2021(AF)2-S3Net: Attentive Feature Fusion with Adaptive Feature Selection for Sparse Semantic Segmentation Networkcited by 164
  22. 2021ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detectioncited by 158
  23. 2023V2V4Real: A Real-world Large-scale Dataset for Vehicle-to-Vehicle Cooperative Perceptioncited by 155
  24. 2024GaussianFormer: Scene as Gaussians for Vision-Based 3D Semantic Occupancy Predictioncited by 155
  25. 2023EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AIcited by 146
  26. 2021FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimationcited by 144
  27. 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 144
  28. 2022Focal Sparse Convolutional Networks for 3D Object Detectioncited by 142
  29. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  30. 2021Delving into Localization Errors for Monocular 3D Object Detectioncited by 138
  31. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  32. 2022Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Cloudscited by 131
  33. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  34. 2023Robo3D: Towards Robust and Reliable 3D Perception against Corruptionscited by 128
  35. 2022Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Datacited by 126
  36. 2022DeepInteraction: 3D Object Detection via Modality Interactioncited by 125
  37. 2023Spherical Transformer for LiDAR-based 3D Recognitioncited by 124
  38. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122

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