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3D Fully Convolutional Network for Vehicle Detection in Point Cloud

arXiv 1611.08069 ↗First posted 24 Nov 2016cs.CV cs.ROcited by 57

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Abstract (arXiv)

2D fully convolutional network has been recently successfully applied to object detection from images. In this paper, we extend the fully convolutional network based detection techniques to 3D and apply it to point cloud data. The proposed approach is verified on the task of vehicle detection from lidar point cloud for autonomous driving. Experiments on the KITTI dataset shows a significant performance improvement over the previous point cloud based detection approaches.

Key facts. Cited by 57 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Nov 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 18; 2022: 16; 2023: 13; 2024: 5; 2025: 4; 2026: 1.

57 papers.

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  1. 2021Offboard 3D Object Detection from Point Cloud Sequencescited by 144
  2. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  3. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  4. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  5. 2022Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Cloudscited by 102
  6. 2021FCAF3D: Fully Convolutional Anchor-Free 3D Object Detectioncited by 97
  7. 2021LookOut: Diverse Multi-Future Prediction and Planning for Self-Drivingcited by 96
  8. 2021Multi-Modal 3D Object Detection in Autonomous Driving: a Surveycited by 63
  9. 2023Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Reviewcited by 57
  10. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  11. 2022Fully Convolutional One-Stage 3D Object Detection on LiDAR Range Imagescited by 56
  12. 2024RangeLDM: Fast Realistic LiDAR Point Cloud Generationcited by 45
38 more
  1. 20214D-Net for Learned Multi-Modal Alignmentcited by 44
  2. 2023UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye Viewcited by 43
  3. 2021Auto4D: Learning to Label 4D Objects from Sequential Point Cloudscited by 42
  4. 2023Super Sparse 3D Object Detectioncited by 32
  5. 2023AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Drivingcited by 32
  6. 2023Fully Sparse Fusion for 3D Object Detectioncited by 29
  7. 2023Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labelingcited by 28
  8. 2022PillarGrid: Deep Learning-based Cooperative Perception for 3D Object Detection from Onboard-Roadside LiDARcited by 25
  9. 2021Revisiting 3D Object Detection From an Egocentric Perspectivecited by 18
  10. 2021See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptationcited by 15
  11. 2022HyperDet3D: Learning a Scene-conditioned 3D Object Detectorcited by 14
  12. 2022itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detectioncited by 14
  13. 2025Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directionscited by 14
  14. 2023MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequencescited by 13
  15. 2021SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimationcited by 12
  16. 2022AGO-Net: Association-Guided 3D Point Cloud Object Detection Networkcited by 12
  17. 2021FAST3D: Flow-Aware Self-Training for 3D Object Detectorscited by 10
  18. 2022TPC: Transformation-Specific Smoothing for Point Cloud Modelscited by 10
  19. 2024Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagerycited by 10
  20. 2021Gated3D: Monocular 3D Object Detection From Temporal Illumination Cuescited by 9
  21. 2022MV6D: Multi-View 6D Pose Estimation on RGB-D Frames Using a Deep Point-wise Voting Networkcited by 9
  22. 2024CT3D++: Improving 3D Object Detection with Keypoint-induced Channel-wise Transformercited by 7
  23. 2021Safety-Oriented Pedestrian Motion and Scene Occupancy Forecastingcited by 6
  24. 2021Real-time 3D Object Detection using Feature Map Flowcited by 5
  25. 2022Transformers for Object Detection in Large Point Cloudscited by 4
  26. 2023SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimationcited by 4
  27. 2022Survey and Systematization of 3D Object Detection Models and Methodscited by 3
  28. 2022Emerging Threats in Deep Learning-Based Autonomous Driving: A Comprehensive Surveycited by 3
  29. 2023Rethinking Voxelization and Classification for 3D Object Detectioncited by 3
  30. 20213D shape sensing and deep learning-based segmentation of strawberriescited by 2
  31. 2022Completing Partial Point Clouds with Outliers by Collaborative Completion and Segmentationcited by 2
  32. 20233D objects and scenes classification, recognition, segmentation, and reconstruction using 3D point cloud data: A reviewcited by 2
  33. 2022Analyzing General-Purpose Deep-Learning Detection and Segmentation Models with Images from a Lidar as a Camera Sensorcited by 1
  34. 2022APSNet: Attention Based Point Cloud Samplingcited by 1
  35. 2023Object Detection in 3D Point Clouds via Local Correlation-Aware Point Embeddingcited by 1
  36. 2023ShaSTA-Fuse: Camera-LiDAR Sensor Fusion to Model Shape and Spatio-Temporal Affinities for 3D Multi-Object Trackingcited by 1
  37. 2023Deep learning for 3D Object Detection and Tracking in Autonomous Driving: A Brief Surveycited by 1
  38. 2024TS40K: a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission Systemcited by 1

50 most cited of 57 All 57 (JSON)