mlsanityData to 7 Oct 2026

AFDet: Anchor Free One Stage 3D Object Detection

arXiv 2006.12671 ↗First posted 23 Jun 2020cs.CVcited by 63

Not on the map. Why?

Abstract (arXiv)

High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to solve it using anchor-based detection methods which come with two drawbacks: post-processing is relatively complex and computationally expensive; tuning anchor parameters is tricky. We are the first to address these drawbacks with an anchor free and Non-Maximum Suppression free one stage detector called AFDet. The entire AFDet can be processed efficiently on a CNN accelerator or a GPU with the simplified post-processing. Without bells and whistles, our proposed AFDet performs competitively with other one stage anchor-based methods on KITTI validation set and Waymo Open Dataset validation set.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Jun 2020.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 23; 2022: 19; 2023: 14; 2024: 3; 2025: 4.

63 papers.

Sort:

By area:

  1. 2023Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecastingcited by 701
  2. 2021Voxel Transformer for 3D Object Detectioncited by 247
  3. 2021Embracing Single Stride 3D Object Detector with Sparse Transformercited by 193
  4. 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 144
  5. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  6. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  7. 2021RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detectioncited by 115
  8. 2022CenterFormer: Center-based Transformer for 3D Object Detectioncited by 99
  9. 2022SWFormer: Sparse Window Transformer for 3D Object Detection in Point Cloudscited by 92
  10. 2021AFDetV2: Rethinking the Necessity of the Second Stage for Object Detection from Point Cloudscited by 88
  11. 2022Fully Sparse 3D Object Detectioncited by 84
  12. 2021Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detectioncited by 79
38 more
  1. 20213D-MAN: 3D Multi-frame Attention Network for Object Detectioncited by 73
  2. 2022Point Density-Aware Voxels for LiDAR 3D Object Detectioncited by 70
  3. 2022MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detectioncited by 65
  4. 2021Multi-Modal 3D Object Detection in Autonomous Driving: a Surveycited by 63
  5. 2021Behind the Curtain: Learning Occluded Shapes for 3D Object Detectioncited by 58
  6. 2023FocalFormer3D : Focusing on Hard Instance for 3D Object Detectioncited by 58
  7. 20213D Siamese Voxel-to-BEV Tracker for Sparse Point Cloudscited by 54
  8. 20213D Object Tracking with Transformercited by 49
  9. 2021Pseudo-labeling for Scalable 3D Object Detectioncited by 32
  10. 2023Super Sparse 3D Object Detectioncited by 32
  11. 2021From Multi-View to Hollow-3D: Hallucinated Hollow-3D R-CNN for 3D Object Detectioncited by 24
  12. 2021BoxeR: Box-Attention for 2D and 3D Transformerscited by 22
  13. 2022Sparse Cross-scale Attention Network for Efficient LiDAR Panoptic Segmentationcited by 22
  14. 2021Pattern-Aware Data Augmentation for LiDAR 3D Object Detectioncited by 15
  15. 2022Point2Seq: Detecting 3D Objects as Sequencescited by 15
  16. 2022itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detectioncited by 14
  17. 2023TrajectoryFormer: 3D Object Tracking Transformer with Predictive Trajectory Hypothesescited by 14
  18. 2021SA-Det3D: Self-Attention Based Context-Aware 3D Object Detectioncited by 13
  19. 2023MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequencescited by 13
  20. 2021SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimationcited by 12
  21. 2023LiDARFormer: A Unified Transformer-based Multi-task Network for LiDAR Perceptioncited by 11
  22. 2021Stereo CenterNet based 3D Object Detection for Autonomous Drivingcited by 10
  23. 2022SpOT: Spatiotemporal Modeling for 3D Object Trackingcited by 10
  24. 2025FSHNet: Fully Sparse Hybrid Network for 3D Object Detectioncited by 9
  25. 2022PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Cloudscited by 7
  26. 20223D Cascade RCNN: High Quality Object Detection in Point Cloudscited by 7
  27. 2022PAI3D: Painting Adaptive Instance-Prior for 3D Object Detectioncited by 6
  28. 2023Generalized Few-Shot 3D Object Detection of LiDAR Point Cloud for Autonomous Drivingcited by 6
  29. 2022Sequential Point Clouds: A Surveycited by 5
  30. 2022OST: Efficient One-stream Network for 3D Single Object Tracking in Point Cloudscited by 5
  31. 2021Real-Time Anchor-Free Single-Stage 3D Detection with IoU-Awarenesscited by 4
  32. 2021A two-stage data association approach for 3D Multi-object Trackingcited by 3
  33. 2023HyperMODEST: Self-Supervised 3D Object Detection with Confidence Score Filteringcited by 3
  34. 2023Object Re-Identification from Point Cloudscited by 3
  35. 2023Frame Fusion with Vehicle Motion Prediction for 3D Object Detectioncited by 3
  36. 2023Fuzzy-NMS: Improving 3D Object Detection with Fuzzy Classification in NMScited by 3
  37. 2024DCDet: Dynamic Cross-based 3D Object Detectorcited by 2
  38. 2025DGFusion: Dual-guided Fusion for Robust Multi-Modal 3D Object Detectioncited by 2

50 most cited of 63 All 63 (JSON)