MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences
Author:
Affiliation:
1. Waymo LLC
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10205140.pdf?arnumber=10205140
Reference63 articles.
1. CramNet: Camera-Radar Fusion with Ray-Constrained Cross-Attention for Robust 3D Object Detection
2. HVNet: Hybrid Voxel Network for LiDAR Based 3D Object Detection
3. DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets
4. Dcms: Motion forecasting with dual consis-tency and multi-pseudo-target supervision;ye;ArXiv Preprint,2022
5. PointPillars: Fast Encoders for Object Detection From Point Clouds
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1. Practical Collaborative Perception: A Framework for Asynchronous and Multi-Agent 3D Object Detection;IEEE Transactions on Intelligent Transportation Systems;2024-09
2. Frame Fusion with Vehicle Motion Prediction for 3D Object Detection;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
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