This is the code for "Exploiting Rigidity Constraints for LiDAR Scene Flow Estimation".
Our model is trained and tested under:
- Python 3.6.9
- NVIDIA GPU + CUDA CuDNN
- PyTorch (torch == 1.5)
- scipy
- tqdm
- sklearn
- numba
- cffi
- pypng
- pptk
Compile the furthest point sampling, grouping and gathering operation for PyTorch. We use the operation from this repo.
cd pointnet2
python setup.py install
cd ../
Set data_root
in the configuration file to SAVE_PATH
in the data preprocess section. Then run
python train.py config_train.yaml
If you use this code for your research, please cite our paper.
@inproceedings{dong2022exploiting,
title={Exploiting rigidity constraints for lidar scene flow estimation},
author={Dong, Guanting and Zhang, Yueyi and Li, Hanlin and Sun, Xiaoyan and Xiong, Zhiwei},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={12776--12785},
year={2022}
}