UniCalli_dataset / README.md
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# UniCalli Dataset
A large-scale Chinese calligraphy dataset with dense annotations, built for the [UniCalli](https://github.com/EnVision-Research/UniCalli) project.
## Overview
The dataset contains Chinese calligraphy images collected from historical works spanning multiple dynasties, covering **95+ calligraphy masters** and **5 major script styles**. Each sample is annotated with bounding boxes, modern text transcriptions, author attribution, and font style labels.
## Webpage
- **Project Page**: [https://envision-research.github.io/UniCalli/](https://envision-research.github.io/UniCalli/)
- **GitHub**: [https://github.com/EnVision-Research/UniCalli](https://github.com/EnVision-Research/UniCalli)
- **HuggingFace Model**: [https://huggingface.co/TSXu/Unicalli_Pro](https://huggingface.co/TSXu/Unicalli_Pro)
- **HuggingFace Demo**: [https://huggingface.co/spaces/TSXu/UniCalli_Dev](https://huggingface.co/spaces/TSXu/UniCalli_Dev)
- **ModelScope**: [https://www.modelscope.cn/models/tianshuo/UniCalli-base](https://www.modelscope.cn/models/tianshuo/UniCalli-base)
- **arXiv**: [https://arxiv.org/abs/2510.13745](https://arxiv.org/abs/2510.13745)
## Citation
If you use this dataset in your research, please cite:
```bibtex
@article{xu2025unicalli,
title={UniCalli: A Unified Diffusion Framework for Column-Level Generation and Recognition of Chinese Calligraphy},
author={Xu, Tianshuo and Wang, Kai and Chen, Zhifei and Wu, Leyi and Wen, Tianshui and Chao, Fei and Chen, Ying-Cong},
journal={arXiv preprint arXiv:2025.13745},
year={2025}
}
```
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license: cc-by-nc-nd-4.0
---