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HDNET: Exploiting HD Maps for 3D Object Detection

arXiv 2012.11704 ↗First posted 21 Dec 2020cs.CVcited by 78

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Abstract (arXiv)

In this paper we show that High-Definition (HD) maps provide strong priors that can boost the performance and robustness of modern 3D object detectors. Towards this goal, we design a single stage detector that extracts geometric and semantic features from the HD maps. As maps might not be available everywhere, we also propose a map prediction module that estimates the map on the fly from raw LiDAR data. We conduct extensive experiments on KITTI as well as a large-scale 3D detection benchmark containing 1 million frames, and show that the proposed map-aware detector consistently outperforms the state-of-the-art in both mapped and un-mapped scenarios. Importantly the whole framework runs at 20 frames per second.

Key facts. Cited by 78 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Dec 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 28; 2022: 19; 2023: 16; 2024: 8; 2025: 4; 2026: 3.

78 papers.

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  1. 2022VectorMapNet: End-to-end Vectorized HD Map Learningcited by 243
  2. 2021PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detectioncited by 232
  3. 2022Unifying Voxel-based Representation with Transformer for 3D Object Detectioncited by 202
  4. 20223D Object Detection for Autonomous Driving: A Comprehensive Surveycited by 132
  5. 2021LiDAR R-CNN: An Efficient and Universal 3D Object Detectorcited by 129
  6. 2022Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipecited by 122
  7. 2021Improving 3D Object Detection with Channel-wise Transformercited by 108
  8. 2021Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Imagescited by 98
  9. 2021LookOut: Diverse Multi-Future Prediction and Planning for Self-Drivingcited by 96
  10. 2022COOPERNAUT: End-to-End Driving with Cooperative Perception for Networked Vehiclescited by 95
  11. 2021FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detectioncited by 92
  12. 2021Depth-conditioned Dynamic Message Propagation for Monocular 3D Object Detectioncited by 84
38 more
  1. 2021SceneGen: Learning to Generate Realistic Traffic Scenescited by 83
  2. 2023End-to-End Vectorized HD-map Construction with Piecewise Bezier Curvecited by 80
  3. 2023Neural Map Prior for Autonomous Drivingcited by 68
  4. 2022Occupancy Flow Fields for Motion Forecasting in Autonomous Drivingcited by 62
  5. 2021Object DGCNN: 3D Object Detection using Dynamic Graphscited by 58
  6. 2023Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Mapscited by 58
  7. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  8. 2022Voxel Field Fusion for 3D Object Detectioncited by 50
  9. 20214D-Net for Learned Multi-Modal Alignmentcited by 44
  10. 2021Auto4D: Learning to Label 4D Objects from Sequential Point Cloudscited by 42
  11. 2022RBGNet: Ray-based Grouping for 3D Object Detectioncited by 40
  12. 2024A Survey on Occupancy Perception for Autonomous Driving: The Information Fusion Perspectivecited by 37
  13. 2021YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detectioncited by 34
  14. 2021Topology Preserving Local Road Network Estimation from Single Onboard Camera Imagecited by 34
  15. 2021Pseudo-labeling for Scalable 3D Object Detectioncited by 32
  16. 2023Implicit Occupancy Flow Fields for Perception and Prediction in Self-Drivingcited by 30
  17. 2023UniBEV: Multi-modal 3D Object Detection with Uniform BEV Encoders for Robustness against Missing Sensor Modalitiescited by 28
  18. 2022Trust, but Verify: Cross-Modality Fusion for HD Map Change Detectioncited by 25
  19. 2021PLUMENet: Efficient 3D Object Detection from Stereo Imagescited by 19
  20. 2021PolarStream: Streaming Lidar Object Detection and Segmentation with Polar Pillarscited by 18
  21. 2021Revisiting 3D Object Detection From an Egocentric Perspectivecited by 18
  22. 2023LiDAR2Map: In Defense of LiDAR-Based Semantic Map Construction Using Online Camera Distillationcited by 18
  23. 2021A Simple and Efficient Multi-task Network for 3D Object Detection and Road Understandingcited by 17
  24. 2023ScalableMap: Scalable Map Learning for Online Long-Range Vectorized HD Map Constructioncited by 16
  25. 2023A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Servicescited by 14
  26. 2021SA-Det3D: Self-Attention Based Context-Aware 3D Object Detectioncited by 13
  27. 2022AGO-Net: Association-Guided 3D Point Cloud Object Detection Networkcited by 12
  28. 2022Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graphcited by 11
  29. 2022Multi-Sem Fusion: Multimodal Semantic Fusion for 3D Object Detectioncited by 11
  30. 2024QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Drivingcited by 11
  31. 2021Investigating Attention Mechanism in 3D Point Cloud Object Detectioncited by 10
  32. 2022THMA: Tencent HD Map AI System for Creating HD Map Annotationscited by 9
  33. 2025Bridging Perspectives: Foundation Model Guided BEV Maps for 3D Object Detection and Trackingcited by 9
  34. 2024CMDA: Cross-Modal and Domain Adversarial Adaptation for LiDAR-Based 3D Object Detectioncited by 8
  35. 2022PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Cloudscited by 7
  36. 2023Improving Online Lane Graph Extraction by Object-Lane Clusteringcited by 7
  37. 2021Safety-Oriented Pedestrian Motion and Scene Occupancy Forecastingcited by 6
  38. 2021MapFusion: A General Framework for 3D Object Detection with HDMapscited by 6

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