mlsanityData to 7 Oct 2026

Ev-3DOD: Pushing the Temporal Boundaries of 3D Object Detection with Event Cameras

arXiv 2502.19630 ↗First posted 26 Feb 2025cs.CVcited by 8

Not on the map. Why?

Abstract (arXiv)

Detecting 3D objects in point clouds plays a crucial role in autonomous driving systems. Recently, advanced multi-modal methods incorporating camera information have achieved notable performance. For a safe and effective autonomous driving system, algorithms that excel not only in accuracy but also in speed and low latency are essential. However, existing algorithms fail to meet these requirements due to the latency and bandwidth limitations of fixed frame rate sensors, e.g., LiDAR and camera. To address this limitation, we introduce asynchronous event cameras into 3D object detection for the first time. We leverage their high temporal resolution and low bandwidth to enable high-speed 3D object detection. Our method enables detection even during inter-frame intervals when synchronized data is unavailable, by retrieving previous 3D information through the event camera. Furthermore, we introduce the first event-based 3D object detection dataset, DSEC-3DOD, which includes ground-truth 3D bounding boxes at 100 FPS, establishing the first benchmark for event-based 3D detectors. The code and dataset are available at https://github.com/mickeykang16/Ev3DOD.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 112 of its 139 references that are in the map. First posted on arXiv 26 Feb 2025.

Builds on

112 of 139 references.

References · 112

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  3. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  4. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,436
  5. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  6. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
  7. 2020Center-based 3D Object Detection and Trackingcited by 1,143
  8. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,040
  9. 2019Event-based Vision: A Surveycited by 1,010
  10. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 939
  11. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 890
  12. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
38 more
  1. 2016Multi-View 3D Object Detection Network for Autonomous Drivingcited by 721
  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. 2019Deep Hough Voting for 3D Object Detection in Point Cloudscited by 648
  5. 2017Frustum PointNets for 3D Object Detection from RGB-D Datacited by 640
  6. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
  7. 2022PETR: Position Embedding Transformation for Multi-View 3D Object Detectioncited by 550
  8. 2018Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Drivingcited by 455
  9. 2019PointPainting: Sequential Fusion for 3D Object Detectioncited by 449
  10. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  11. 2020Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detectioncited by 409
  12. 2021Multi-Modal Fusion Transformer for End-to-End Autonomous Drivingcited by 372
  13. 2020Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloudcited by 335
  14. 2022BEVFusion: A Simple and Robust LiDAR-Camera Fusion Frameworkcited by 334
  15. 2021Categorical Depth Distribution Network for Monocular 3D Object Detectioncited by 326
  16. 2017Joint 3D Proposal Generation and Object Detection from View Aggregationcited by 325
  17. 2018Unsupervised Event-based Learning of Optical Flow, Depth, and Egomotioncited by 304
  18. 2021DSEC: A Stereo Event Camera Dataset for Driving Scenarioscited by 297
  19. 2019STD: Sparse-to-Dense 3D Object Detector for Point Cloudcited by 282
  20. 2020Deep Continuous Fusion for Multi-Sensor 3D Object Detectioncited by 263
  21. 2021Is Pseudo-Lidar needed for Monocular 3D Object detection?cited by 248
  22. 2021Voxel Transformer for 3D Object Detectioncited by 247
  23. 2022DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detectioncited by 224
  24. 2023VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Trackingcited by 221
  25. 2020Multi-Task Multi-Sensor Fusion for 3D Object Detectioncited by 203
  26. 2020SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimationcited by 202
  27. 2022Unifying Voxel-based Representation with Transformer for 3D Object Detectioncited by 202
  28. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  29. 2021Embracing Single Stride 3D Object Detector with Sparse Transformercited by 193
  30. 2019Pseudo-LiDAR++: Accurate Depth for 3D Object Detection in Autonomous Drivingcited by 188
  31. 2020Learning to Detect Objects with a 1 Megapixel Event Cameracited by 184
  32. 2017PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimationcited by 170
  33. 2019Stereo R-CNN based 3D Object Detection for Autonomous Drivingcited by 163
  34. 2019Video to Events: Recycling Video Datasets for Event Camerascited by 162
  35. 2022Recurrent Vision Transformers for Object Detection with Event Camerascited by 158
  36. 2021Geometry Uncertainty Projection Network for Monocular 3D Object Detectioncited by 155
  37. 2021What Makes Multi-modal Learning Better than Single (Provably)cited by 151
  38. 2020CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detectioncited by 147

50 most cited of 112 All 112 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 5.

8 papers.

  1. 2025Unleashing the Temporal Potential of Stereo Event Cameras for Continuous-Time 3D Object Detectioncited by 3
  2. 2026Event6D: Event-based Novel Object 6D Pose Trackingcited by 2
  3. 2026DSERT-RoLL: Robust Multi-Modal Perception for Diverse Driving Conditions with Stereo Event-RGB-Thermal Cameras, 4D Radar, and Dual-LiDARcited by 2
  4. 2025Dynamic Graph Induced Contour-aware Heat Conduction Network for Event-based Object Detectioncited by 1
  5. 2025Cross-Modal Retrieval with Cauchy-Schwarz Divergencecited by 0
  6. 2026DeepIPCv3: Event-Aware Multi-Modal Sensor Fusion for Sudden Pedestrian Crossing Avoidancecited by 0
  7. 2026GoStop: Reinforcement Learning for Adaptive Temporal Aggregation in Event-Based Feature Trackingcited by 0
  8. 2026Neuromorphic Object Detection: An In-Depth Study and Future Directionscited by 0