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update eccv26 papers synflow and uniflow
Update a community improvement plan later.
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README.md

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💞 If you find [*OpenSceneFlow*](https://github.com/KTH-RPL/OpenSceneFlow) useful to your research, please cite [**our works** 📖](#cite-us) and [give a star 🌟](https://github.com/KTH-RPL/OpenSceneFlow) as encouragement. (੭ˊ꒳​ˋ)੭✧
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[OpenSceneFlow](https://github.com/KTH-RPL/OpenSceneFlow) is a codebase for point cloud scene flow estimation with pre-trained models and datasets available on [HuggingFace](https://huggingface.co/kin-zhang/OpenSceneFlow).
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<!-- It is also an official implementation of the following papers (sorted by the time of publication): -->
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It is also an official implementation of the following papers:
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- **SynFlow: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data**
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*Qingwen Zhang, Xiaomeng Zhu, Chenhan Jiang, Patric Jensfelt*
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European Conference on Computer Vision (**ECCV**) 2026
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[ Pretrain ] [ Synthesis ] - [ [arXiv](https://arxiv.org/abs/2604.09411) ] [ [Project](https://kin-zhang.github.io/SynFlow/) ]&rarr; [here](https://github.com/Kin-Zhang/SynFlow)
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- **TeFlow: Enabling Multi-frame Supervision for Self-Supervised Feed-forward Scene Flow Estimation**
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*Qingwen Zhang, Chenhan Jiang, Xiaomeng Zhu, Yunqi Miao, Yushan Zhang, Olov Andersson, Patric Jensfelt*
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Conference on Computer Vision and Pattern Recognition (**CVPR**) 2026 - Highlight
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IEEE Transactions on Robotics (**T-RO**) 2025
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[ Strategy ] [ Self-Supervised ] - [ [arXiv](https://arxiv.org/abs/2503.00803) ] [ [Project](https://kin-zhang.github.io/HiMo/) ] &rarr; [here](#seflow-1)
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- **SynFlow: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data**
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*Qingwen Zhang, Xiaomeng Zhu, Chenhan Jiang, Patric Jensfelt*
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Preprint arXiv 2026
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[ Pretrain ] [ Synthesis ] - [ [arXiv](https://arxiv.org/abs/2604.09411) ] [ [Project](https://kin-zhang.github.io/SynFlow/) ]
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- **SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving**
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*Qingwen Zhang, Yi Yang, Peizheng Li, Olov Andersson, Patric Jensfelt*
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European Conference on Computer Vision (**ECCV**) 2024
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[ Strategy ] [ Self-Supervised ] - [ [arXiv](https://arxiv.org/abs/2407.01702) ] [ [Project](https://github.com/KTH-RPL/SeFlow) ] &rarr; [here](#seflow)
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- **UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles**
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*Siyi Li, Qingwen Zhang, Ishan Khatri, Kyle Vedder, Eric Eaton, Deva Ramanan, Neehar Peri*
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Preprint arXiv 2026
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European Conference on Computer Vision (**ECCV**) 2026
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[ Strategy ] [ Supervised ] - [ [arXiv](https://arxiv.org/abs/2511.18254) ] [ [Project](https://lisiyi777.github.io/UniFlow/) ]&rarr; [here](https://github.com/lisiyi777/UniFlow)
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- **DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance**
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International Conference on Robotics and Automation (**ICRA**) 2025
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[ Backbone ] [ Supervised ] - [ [arXiv](https://arxiv.org/abs/2501.17821) ] [ [Project](https://github.com/KTH-RPL/SSF) ] &rarr; [here](#ssf)
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- **SeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving**
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*Qingwen Zhang, Yi Yang, Peizheng Li, Olov Andersson, Patric Jensfelt*
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European Conference on Computer Vision (**ECCV**) 2024
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[ Strategy ] [ Self-Supervised ] - [ [arXiv](https://arxiv.org/abs/2407.01702) ] [ [Project](https://github.com/KTH-RPL/SeFlow) ] &rarr; [here](#seflow)
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- **DeFlow: Decoder of Scene Flow Network in Autonomous Driving**
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*Qingwen Zhang, Yi Yang, Heng Fang, Ruoyu Geng, Patric Jensfelt*
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International Conference on Robotics and Automation (**ICRA**) 2024
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```bibtex
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@inproceedings{zhang2026teflow,
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title = {{TeFlow}: Enabling Multi-frame Supervision for Self-Supervised Feed-forward Scene Flow Estimation},
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author={Zhang, Qingwen and Jiang, Chenhan and Zhu, Xiaomeng and Miao, Yunqi and Zhang, Yushan and Andersson, Olov and Jensfelt, Patric},
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author = {Zhang, Qingwen and Jiang, Chenhan and Zhu, Xiaomeng and Miao, Yunqi and Zhang, Yushan and Andersson, Olov and Jensfelt, Patric},
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year = {2026},
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booktitle = {Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
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pages = {},
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pages = {3667-3676},
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}
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@article{zhang2026synflow,
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title={{SynFlow}: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data},
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author={Zhang, Qingwen and Zhu, Xiaomeng and Jiang, Chenhan and Jensfelt, Patric},
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journal={arXiv preprint arXiv:2604.09411},
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year={2026}
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}
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@inproceedings{zhang2025deltaflow,
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title={{DeltaFlow}: An Efficient Multi-frame Scene Flow Estimation Method},
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author={Zhang, Qingwen and Zhu, Xiaomeng and Zhang, Yushan and Cai, Yixi and Andersson, Olov and Jensfelt, Patric},
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booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
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year={2025},
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url={https://openreview.net/forum?id=T9qNDtvAJX}
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}
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@article{zhang2025himo,
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title={{HiMo}: High-Speed Objects Motion Compensation in Point Cloud},
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author={Zhang, Qingwen and Khoche, Ajinkya and Yang, Yi and Ling, Li and Mansouri, Sina Sharif and Andersson, Olov and Jensfelt, Patric},
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journal={IEEE Transactions on Robotics},
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year={2025},
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volume={41},
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pages={5896-5911},
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doi={10.1109/TRO.2025.3619042}
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}
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@inproceedings{zhang2024seflow,
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author={Zhang, Qingwen and Yang, Yi and Li, Peizheng and Andersson, Olov and Jensfelt, Patric},
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pages={2105-2111},
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doi={10.1109/ICRA57147.2024.10610278}
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}
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@article{zhang2025himo,
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title={{HiMo}: High-Speed Objects Motion Compensation in Point Cloud},
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author={Zhang, Qingwen and Khoche, Ajinkya and Yang, Yi and Ling, Li and Mansouri, Sina Sharif and Andersson, Olov and Jensfelt, Patric},
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journal={IEEE Transactions on Robotics},
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year={2025},
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volume={41},
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pages={5896-5911},
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doi={10.1109/TRO.2025.3619042}
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}
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@inproceedings{zhang2025deltaflow,
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title={{DeltaFlow}: An Efficient Multi-frame Scene Flow Estimation Method},
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author={Zhang, Qingwen and Zhu, Xiaomeng and Zhang, Yushan and Cai, Yixi and Andersson, Olov and Jensfelt, Patric},
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booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
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year={2025},
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url={https://openreview.net/forum?id=T9qNDtvAJX}
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}
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@article{zhang2026synflow,
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title={{SynFlow}: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data},
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author={Zhang, Qingwen and Zhu, Xiaomeng and Jiang, Chenhan and Jensfelt, Patric},
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journal={arXiv preprint arXiv:2604.09411},
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year={2026}
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}
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```
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And our excellent collaborators works contributed to this codebase also:

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