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README.md

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+---
+task_categories:
+- image-to-video
+license: cc-by-4.0
+language:
+- en
+tags:
+- panoramic
+- video-generation
+- motion-control
+- 360-degree
+- optical-flow
+- computer-vision
+- diffusion
+---
+
+# PanFlow Dataset
+
+The PanFlow dataset supports the research presented in the paper **[PanFlow: Decoupled Motion Control for Panoramic Video Generation](https://huggingface.co/papers/2512.00832)**.
+
+PanFlow is a novel framework for controllable 360° panoramic video generation that decouples motion input into two interpretable components: rotation flow and derotated flow. This dataset is a large-scale, motion-rich panoramic video dataset with frame-level pose and optical flow annotations, curated to enable precise motion control, produce loop-consistent panoramas, and support applications such as motion transfer and panoramic video editing.
+
+**Paper:** [https://huggingface.co/papers/2512.00832](https://huggingface.co/papers/2512.00832)
+**Code:** [https://github.com/chengzhag/PanFlow](https://github.com/chengzhag/PanFlow)
+**Video Overview:** [https://www.youtube.com/watch?v=sFTWwlHjNtg](https://www.youtube.com/watch?v=sFTWwlHjNtg)
+
+<p align="center">
+  <img src="images/flow.png" alt="flow" width="400">
+</p>
+
+By conditioning diffusion on spherical-warped motion noise, PanFlow enables precise motion control, produces loop-consistent panoramas, and supports applications such as motion transfer:
+
+<p align="center">
+  <img src="images/transfer.gif" alt="flow" width="860">
+</p>
+
+and panoramic video editing:
+
+<p align="center">
+  <img src="images/editing.gif" alt="flow" width="860">
+</p>
+
+## Dataset Structure and Details
+
+The PanFlow dataset provides camera pose annotations for 300k clips. It also includes pre-generated latent and noise cache for a filtered subset to speed up training.
+
+The underlying video data is derived from the [360-1M dataset](https://github.com/MattWallingford/360-1M), which consists of YouTube videos licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
+
+## Citation
+
+If you use the PanFlow dataset in your research, please cite the original paper:
+
+```bibtex
+@inproceedings{zhang2025panflow,
+  title={PanFlow: Decoupled Motion Control for Panoramic Video Generation},
+  author={Zhang, Cheng and Liang, Hanwen and Chen, Donny Y and Wu, Qianyi and Plataniotis, Konstantinos N and Gambardella, Camilo Cruz and Cai, Jianfei},
+  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
+  year={2026}
+}
+```

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