The official implementation of the paper:
P2P: Part-to-Part Motion Cues Guide a Strong Tracking Framework for LiDAR Point Clouds
Jiahao Nie, Fei Xie, Sifan Zhou, Xueyi Zhou, Dong-Kyu Chae, Zhiwei He.
📜 [technical report], 🤗 [model weights]
P2P is a strong tracking framework for 3D SOT on LiDAR point clouds that have:
- Elegant tracking pipeline.
- SOTA performance on KITTI, NuScenes and Waymo.
- High efficiency.
Important
If you have any question for our codes or model weights, please feel free to concat me at jhnie@hdu.edu.cn.
- [2024/07/10] We released the arxiv version at here.
- [2024/07/07] We released the installation, training, and testing details.
- [2024/07/06] We released the implementation of our model.
- All caterogy model weights of point and voxel versions trained on KITTI, Nuscenes.
Our implementation is based on Open3DSOT, BEVTrack and MMDetection3D. Thanks for the great open-source work!
If any parts of our paper and code help your research, please consider citing us and giving a star to our repository.
@article{p2p,
title={P2P: Part-to-Part Motion Cues Guide a Strong Tracking Framework for LiDAR Point Clouds},
year={2024}
}