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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/). We provide a 720P version on [360-1M-720P](https://huggingface.co/datasets/chengzhag/360-1M-720P).
## 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}
}
``` |