update teflow ckpt.

update deltaflow-av2-longadp ckpt for training-free long-range.

README.md

@@ -28,6 +28,7 @@ Here we upload our demo data and checkpoint for the community.
 You can try following methods in [our OpenSceneFlow](https://github.com/KTH-RPL/OpenSceneFlow) without any effort to make your own benchmark.
 
 Officially:
+- [x] [TeFlow](https://arxiv.org/abs/2602.19053) (Ours 🚀): CVPR 2026
 - [x] [DeltaFlow](https://arxiv.org/abs/2508.17054) (Ours 🚀): NeurIPS 2025, spotlight
 - [x] [HiMo (SeFlow++)](https://arxiv.org/abs/2503.00803) (Ours 🚀): T-RO 2025
 - [x] [VoteFlow](https://arxiv.org/abs/2503.22328): CVPR 2025
@@ -38,12 +39,13 @@ Officially:
 
 <details> <summary> Reoriginse to our codebase:</summary>
   
-- [x] [FastFlow3d](https://arxiv.org/abs/2103.01306): RA-L 2021
-- [x] [ZeroFlow](https://arxiv.org/abs/2305.10424): ICLR 2024, their pre-trained weight can covert into our format easily through [the script](https://github.com/KTH-RPL/OpenSceneFlow/tools/zerof2ours.py).
-- [x] [NSFP](https://arxiv.org/abs/2111.01253): NeurIPS 2021, faster 3x than original version because of [our CUDA speed up](https://github.com/KTH-RPL/OpenSceneFlow/assets/cuda/README.md), same (slightly better) performance. Done coding, public after review.
-- [x] [FastNSF](https://arxiv.org/abs/2304.09121): ICCV 2023.
-- [ ] [ICP-Flow](https://arxiv.org/abs/2402.17351): CVPR 2024. Done coding, wait after review approval.
-- [ ] ... more on the way
+- [x] [FastFlow3D](https://arxiv.org/abs/2103.01306): RA-L 2021, a basic backbone model.
+- [x] [ZeroFlow](https://arxiv.org/abs/2305.10424): ICLR 2024, their pre-trained weight can covert into our format easily through [the script](tools/zerof2ours.py).
+- [x] [NSFP](https://arxiv.org/abs/2111.01253): NeurIPS 2021, faster 3x than original version because of [our CUDA speed up](assets/cuda/README.md), same (slightly better) performance.
+- [x] [FastNSF](https://arxiv.org/abs/2304.09121): ICCV 2023. SSL Optimization-based.
+- [x] [ICP-Flow](https://arxiv.org/abs/2402.17351): CVPR 2024. SSL Optimization-based.
+- [ ] [Floxels](https://arxiv.org/abs/2503.04718): CVPR 2025. SSL optimization-based. coding now but not yet ready for release as lower performance than reported. check [branch code](https://github.com/Kin-Zhang/OpenSceneFlow/tree/feature/floxels) for more details.
+- [ ] [EulerFlow](https://arxiv.org/abs/2410.02031): ICLR 2025. SSL optimization-based. In my plan, haven't coding yet.
 
 </details>
 
@@ -55,14 +57,21 @@ The tree of uploaded files:
 * [waymo_map.tar.gz](https://huggingface.co/kin-zhang/OpenSceneFlow/blob/main/waymo_map.tar.gz): to successfully process waymo data with ground segmentation included to unified h5 file. Check usage in [this README](https://github.com/KTH-RPL/SeFlow/blob/main/dataprocess/README.md#waymo-dataset).
 * [demo_data.zip](https://huggingface.co/kin-zhang/OpenSceneFlow/blob/main/demo_data.zip): 1st version (will deprecated later) 613Mb, a mini-dataset for user to quickly run train/val code. Check usage in [this section](https://github.com/KTH-RPL/OpenSceneFlow?tab=readme-ov-file#1-run--train).
 
-All test result reports can be found [v2 leaderboard](https://github.com/KTH-RPL/DeFlow/discussions/6) 
-and [v1 leaderboard](https://github.com/KTH-RPL/DeFlow/discussions/2).
+<!-- All test result reports can be found [v2 leaderboard](https://github.com/KTH-RPL/DeFlow/discussions/6)  -->
+<!-- and [v1 leaderboard](https://github.com/KTH-RPL/DeFlow/discussions/2). -->
 
 ## Cite Us
 
 *OpenSceneFlow* is designed by [Qingwen Zhang](https://kin-zhang.github.io/) from DeFlow and SeFlow project. If you find it useful, please cite our works:
 
 ```bibtex
+@inproceedings{zhang2026teflow,
+  title = {{TeFlow}: Enabling Multi-frame Supervision for Self-Supervised Feed-forward Scene Flow Estimation},
+  author={Zhang, Qingwen and Jiang, Chenhan and Zhu, Xiaomeng and Miao, Yunqi and Zhang, Yushan and Andersson, Olov and Jensfelt, Patric},
+  year = {2026},
+  booktitle = {Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
+  pages = {},
+}
 @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},
@@ -81,27 +90,35 @@ and [v1 leaderboard](https://github.com/KTH-RPL/DeFlow/discussions/2).
   doi={10.1109/ICRA57147.2024.10610278}
 }
 @article{zhang2025himo,
-    title={HiMo: High-Speed Objects Motion Compensation in Point Clouds},
-    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},
+  title={{HiMo}: High-Speed Objects Motion Compensation in Point Cloud},
+  author={Zhang, Qingwen and Khoche, Ajinkya and Yang, Yi and Ling, Li and Mansouri, Sina Sharif and Andersson, Olov and Jensfelt, Patric},
+  journal={IEEE Transactions on Robotics}, 
+  year={2025},
+  volume={41},
+  pages={5896-5911},
+  doi={10.1109/TRO.2025.3619042}
 }
-@article{zhang2025deltaflow,
-    title={{DeltaFlow}: An Efficient Multi-frame Scene Flow Estimation Method},
-    author={Zhang, Qingwen and Zhu, Xiaomeng and Zhang, Yushan and Cai, Yixi and Andersson, Olov and Jensfelt, Patric},
-    year={2025},
-    journal={arXiv preprint arXiv:2508.17054},
+@inproceedings{zhang2025deltaflow,
+  title={{DeltaFlow}: An Efficient Multi-frame Scene Flow Estimation Method},
+  author={Zhang, Qingwen and Zhu, Xiaomeng and Zhang, Yushan and Cai, Yixi and Andersson, Olov and Jensfelt, Patric},
+  booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
+  year={2025},
+  url={https://openreview.net/forum?id=T9qNDtvAJX}
 }
 ```
 
-And our excellent collaborators works as followings:
+And our excellent collaborators works contributed to this codebase also:
 
 ```bibtex
-@inproceedings{lin2025voteflow,
-  title={VoteFlow: Enforcing Local Rigidity in Self-Supervised Scene Flow},
-  author={Lin, Yancong and Wang, Shiming and Nan, Liangliang and Kooij, Julian and Caesar, Holger},
-  booktitle={CVPR},
-  year={2025},
+@article{khoche2026dogflow,
+  author={Khoche, Ajinkya and Zhang, Qingwen and Cai, Yixi and Mansouri, Sina Sharif and Jensfelt, Patric},
+  journal = {IEEE Robotics and Automation Letters},
+  title = {{DoGFlow}: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance},
+  year = {2026},
+  volume = {11},
+  number = {3},
+  pages = {3836-3843},
+  doi = {10.1109/LRA.2026.3662592},
 }
 @article{kim2025flow4d,
   author={Kim, Jaeyeul and Woo, Jungwan and Shin, Ukcheol and Oh, Jean and Im, Sunghoon},
@@ -113,11 +130,19 @@ And our excellent collaborators works as followings:
   pages={3462-3469},
   doi={10.1109/LRA.2025.3542327}
 }
-@article{khoche2025ssf,
-  title={SSF: Sparse Long-Range Scene Flow for Autonomous Driving},
+@inproceedings{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}
+  booktitle={2025 IEEE International Conference on Robotics and Automation (ICRA)}, 
+  year={2025},
+  pages={6394-6400},
+  doi={10.1109/ICRA55743.2025.11128770}
+}
+@inproceedings{lin2025voteflow,
+  title={VoteFlow: Enforcing Local Rigidity in Self-Supervised Scene Flow},
+  author={Lin, Yancong and Wang, Shiming and Nan, Liangliang and Kooij, Julian and Caesar, Holger},
+  booktitle={CVPR},
+  year={2025},
 }
 ```
 

deltaflow/deltaflow-av2-longadp.ckpt

@@ -0,0 +1,3 @@
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+size 239609425

teflow/README.md

@@ -0,0 +1,5 @@
+teflow ckpt, in-domain self-supervised training.
+
+- av2
+- nus
+- waymo

teflow/teflow-av2.ckpt

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+size 239574067

teflow/teflow-nus.ckpt

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+oid sha256:6ec8491175ab40debc7d0427af821f2056b883fadb24260c18720989e13615c8
+size 239573875

teflow/teflow-waymo.ckpt

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