Learning to Write Stylized Chinese Characters by Reading a Handful of Examples

Learning to Write Stylized Chinese Characters by Reading a Handful of Examples

Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Main track. Pages 920-927. https://doi.org/10.24963/ijcai.2018/128

Automatically writing stylized characters is an attractive yet challenging task, especially for Chinese characters with complex shapes and structures. Most current methods are restricted to generate stylized characters already present in the training set, but required to retrain the model when generating characters of new styles. In this paper, we develop a novel framework of Style-Aware Variational Auto-Encoder (SA-VAE), which disentangles the content-relevant and style-relevant components of a Chinese character feature with a novel intercross pair-wise optimization method. In this case, our method can generate Chinese characters flexibly by reading a few examples. Experiments demonstrate that our method has a powerful one-shot/few-shot generalization ability by inferring the style representation, which is the first attempt to learn to write new-style Chinese characters by observing only one or a few examples. 
Keywords:
Computer Vision: Statistical Methods and Machine Learning
Computer Vision: Computer Vision