Scene Flow Models for Autonomous Driving Dataset
π If you find OpenSceneFlow useful to your research, please cite our works π and give a star π as encouragement. (ΰ©Λκ³βΛ)ΰ©β§
OpenSceneFlow is a codebase for point cloud scene flow estimation. Please check the usage on KTH-RPL/OpenSceneFlow.
The files we included and all test result reports can be found v2 leaderboard and v1 leaderboard.
- [ModelName_best].ckpt: means the model evaluated in the public leaderboard page provided by authors or our retrained with the best parameters.
- demo_data.zip: 613Mb, a mini-dataset for user to quickly run train/val code. Check usage in this section.
- waymo_map.tar.gz: to successfully process waymo data with ground segmentation included to unified h5 file. Check usage in this README.
π One repository, All methods!
You can try following methods in our code without any effort to make your own benchmark.- SSF (Ours π): ICRA 2025
- Flow4D: RA-L 2025
- SeFlow (Ours π): ECCV 2024
- DeFlow (Ours π): ICRA 2024
- FastFlow3d: RA-L 2021
- ZeroFlow: ICLR 2024, their pre-trained weight can covert into our format easily through the script.
- NSFP: NeurIPS 2021, faster 3x than original version because of our CUDA speed up, same (slightly better) performance. Done coding, public after review.
- FastNSF: ICCV 2023. Done coding, public after review.
- ... more on the way
Cite Us
OpenSceneFlow is designed by Qingwen Zhang from DeFlow and SeFlow project. If you find it useful, please cite our works:
@inproceedings{zhang2024seflow,
author={Zhang, Qingwen and Yang, Yi and Li, Peizheng and Andersson, Olov and Jensfelt, Patric},
title={{SeFlow}: A Self-Supervised Scene Flow Method in Autonomous Driving},
booktitle={European Conference on Computer Vision (ECCV)},
year={2024},
pages={353β369},
organization={Springer},
doi={10.1007/978-3-031-73232-4_20},
}
@inproceedings{zhang2024deflow,
author={Zhang, Qingwen and Yang, Yi and Fang, Heng and Geng, Ruoyu and Jensfelt, Patric},
booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)},
title={{DeFlow}: Decoder of Scene Flow Network in Autonomous Driving},
year={2024},
pages={2105-2111},
doi={10.1109/ICRA57147.2024.10610278}
}
@article{zhang2025himu,
title={HiMo: High-Speed Objects Motion Compensation in Point Cloud},
author={Zhang, Qingwen and Khoche, Ajinkya and Yang, Yi and Ling, Li and Sina, Sharif Mansouri and Andersson, Olov and Jensfelt, Patric},
year={2025},
journal={arXiv preprint arXiv:2503.00803},
}
And our excellent collaborators works as followings:
@article{kim2025flow4d,
author={Kim, Jaeyeul and Woo, Jungwan and Shin, Ukcheol and Oh, Jean and Im, Sunghoon},
journal={IEEE Robotics and Automation Letters},
title={Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation},
year={2025},
volume={10},
number={4},
pages={3462-3469},
doi={10.1109/LRA.2025.3542327}
}
@article{khoche2025ssf,
title={SSF: Sparse Long-Range Scene Flow for Autonomous Driving},
author={Khoche, Ajinkya and Zhang, Qingwen and Sanchez, Laura Pereira and Asefaw, Aron and Mansouri, Sina Sharif and Jensfelt, Patric},
journal={arXiv preprint arXiv:2501.17821},
year={2025}
}
Feel free to contribute your method and add your bibtex here by pull request!
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