mlsanityData to 7 Oct 2026

Class-balanced Grouping and Sampling for Point Cloud 3D Object Detection

arXiv 1908.09492 ↗First posted 26 Aug 2019cs.CVcited by 350

Not on the map. Why?

Abstract (arXiv)

This report presents our method which wins the nuScenes3D Detection Challenge [17] held in Workshop on Autonomous Driving(WAD, CVPR 2019). Generally, we utilize sparse 3D convolution to extract rich semantic features, which are then fed into a class-balanced multi-head network to perform 3D object detection. To handle the severe class imbalance problem inherent in the autonomous driving scenarios, we design a class-balanced sampling and augmentation strategy to generate a more balanced data distribution. Furthermore, we propose a balanced group-ing head to boost the performance for the categories withsimilar shapes. Based on the Challenge results, our methodoutperforms the PointPillars [14] baseline by a large mar-gin across all metrics, achieving state-of-the-art detection performance on the nuScenes dataset. Code will be released at CBGS.

Key facts. Cited by 350 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Aug 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 28; 2022: 79; 2023: 102; 2024: 82; 2025: 40; 2026: 19.

350 papers.

Sort:

By area:

  1. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
  2. 2021BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-Viewcited by 711
  3. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 655
  4. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
  5. 2022PETR: Position Embedding Transformation for Multi-View 3D Object Detectioncited by 550
  6. 2022TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformerscited by 464
  7. 2021FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detectioncited by 444
  8. 2022PETRv2: A Unified Framework for 3D Perception from Multi-Camera Imagescited by 351
  9. 2022BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detectioncited by 340
  10. 2022BEVFusion: A Simple and Robust LiDAR-Camera Fusion Frameworkcited by 334
  11. 2023Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detectioncited by 313
  12. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
38 more
  1. 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Trackingcited by 221
  2. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  3. 2022BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Drivingcited by 191
  4. 2022Time Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detectioncited by 177
  5. 2021Multimodal Virtual Point 3D Detectioncited by 166
  6. 2022Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusioncited by 161
  7. 2023SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videoscited by 149
  8. 2022Focal Sparse Convolutional Networks for 3D Object Detectioncited by 142
  9. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  10. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  11. 2022Vision-Centric BEV Perception: A Surveycited by 126
  12. 2022DeepInteraction: 3D Object Detection via Modality Interactioncited by 125
  13. 2023Spherical Transformer for LiDAR-based 3D Recognitioncited by 124
  14. 2023DSVT: Dynamic Sparse Voxel Transformer with Rotated Setscited by 122
  15. 2021Panoptic-PolarNet: Proposal-free LiDAR Point Cloud Panoptic Segmentationcited by 107
  16. 2022PillarNet: Real-Time and High-Performance Pillar-based 3D Object Detectioncited by 99
  17. 2022CenterFormer: Center-based Transformer for 3D Object Detectioncited by 99
  18. 2023FB-BEV: BEV Representation from Forward-Backward View Transformationscited by 98
  19. 2021FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detectioncited by 92
  20. 2023Sparse4D v2: Recurrent Temporal Fusion with Sparse Modelcited by 92
  21. 2021AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Cloudscited by 88
  22. 2022MonoDETR: Depth-guided Transformer for Monocular 3D Object Detectioncited by 85
  23. 2023SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detectioncited by 83
  24. 2024RCBEVDet: Radar-camera Fusion in Bird's Eye View for 3D Object Detectioncited by 82
  25. 2023CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perceptioncited by 81
  26. 2021Monocular Quasi-Dense 3D Object Trackingcited by 80
  27. 2021M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformerscited by 74
  28. 2022LidarMultiNet: Towards a Unified Multi-Task Network for LiDAR Perceptioncited by 74
  29. 2023BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detectioncited by 74
  30. 2023UniPAD: A Universal Pre-training Paradigm for Autonomous Drivingcited by 73
  31. 2023FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformercited by 72
  32. 2022LargeKernel3D: Scaling up Kernels in 3D Sparse CNNscited by 71
  33. 2023Sparse4D v3: Advancing End-to-End 3D Detection and Trackingcited by 69
  34. 2023Cross Modal Transformer: Towards Fast and Robust 3D Object Detectioncited by 68
  35. 2022MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detectioncited by 62
  36. 2023FocalFormer3D : Focusing on Hard Instance for 3D Object Detectioncited by 58
  37. 2024IS-Fusion: Instance-Scene Collaborative Fusion for Multimodal 3D Object Detectioncited by 57
  38. 2021DEFT: Detection Embeddings for Trackingcited by 56

50 most cited of 350 All 350 (JSON)