---
license: mit
library_name: pytorch
tags:
- computer-vision
- 3d-reconstruction
- gaussian-splatting
- head-avatar
- animation
- cvpr-2026
---

# UIKA

This repository hosts the released model weights and auxiliary assets for **UIKA: Fast Universal Head Avatar from Pose-Free Images**.

UIKA is a feed-forward model for creating animatable 3D Gaussian head avatars from pose-free inputs. It supports a single reference image, multiple images of the same identity, or smartphone-style video captures. Use these files together with the official PyTorch code:

- Code: https://github.com/ant-research/UIKA
- Paper: https://arxiv.org/abs/2601.07603
- Project page: https://zijian-wu.github.io/uika-page/

## Files

- `uika.safetensors` - main UIKA checkpoint. The official inference config expects it at `model_zoo/uika/uika.safetensors`.
- `fuvt_15k.safetensors` - FUVT UV-estimation module checkpoint used by UIKA.
- `human_parametric_models.tar` - human parametric model assets required by the pipeline. Third-party assets may have separate license terms.
- `ref_motion_example.tar` - example reference/motion assets for testing inference.

## License

The UIKA-authored code and the released UIKA/FUVT checkpoints are released under the MIT License. Third-party model weights, datasets, and human parametric model assets remain subject to their own licenses and access terms. Review the official repository's third-party notices before redistribution or commercial use.

## Citation

If you use UIKA in your work, please cite:

```bibtex
@inproceedings{wu2026uika,
    title     = {UIKA: Fast Universal Head Avatar from Pose-Free Images},
    author    = {Wu, Zijian and Zhou, Boyao and Hu, Liangxiao and Liu, Hongyu and Sun, Yuan and Wang, Xuan and Cao, Xun and Shen, Yujun and Zhu, Hao},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
    year      = {2026}
}
```