🖌️ UniCalli

A Unified Diffusion Framework for Column-Level Generation and Recognition of Chinese Calligraphy

UniCalli is a groundbreaking unified diffusion framework that addresses column-level generation of Chinese calligraphy. Unlike existing methods that focus on isolated character generation or compromise calligraphic correctness for page-level synthesis, UniCalli integrates both recognition and generation tasks in a single model, achieving superior results in both stylistic fidelity and structural accuracy.

UniCalli 是一个突破性的统一扩散模型框架,解决了中国书法列级生成问题。与现有方法专注于孤立字符生成或在页面级合成中牺牲书法正确性不同, UniCalli 在单一模型中集成了识别和生成能力,使得其在风格保真度和结构准确性方面都取得了卓越的成果。

Pipeline

UniCalli Pipeline

Citation

If you find UniCalli useful in your research, please cite our paper:

@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:2510.13745},
  year={2025}
}