DCFont: An End-To-End Deep Chinese Font Generation System

Yue Jiang Zhouhui Lian Yingmin Tang Jianguo Xiao

 Institute of Computer Science and Technology, Peking University, Beijing, P.R.China

 {yue.jiang, lianzhouhui, tangyingmin, xiaojianguo}@pku.edu.cn

Abstract

Building a complete personalized Chinese font library for an ordinary person is a tough task due to the existence of huge amounts of characters with complicated structures. Yet, existing automatic font generation methods still have many drawbacks. To address those problems, this paper proposes an end-to-end learning system, DCFont, to automatically generate the whole GB2312 font library that consists of 6763 Chinese characters from a small number (e.g., 775) of characters written by the user. Our system has two major advantages. On the one hand, the system works in an end-toend manner, which means that human interventions during offline training and online generating periods are not required. On the other hand, a novel deep neural network architecture is designed to solve the font feature reconstruction and handwriting synthesis problems through adversarial training, which requires fewer input data but obtains more realistic and high-quality synthesis results compared to other deep learning based approaches. Experimental results verify the superiority of our method against the state of the art.

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DCFont: An End-To-End Deep Chinese Font Generation System   Yue Jiang, Zhouhui Lian, Yingmin Tang, Jianguo Xiao      [ Pre-print 1.99MB]  [ Supplementary_materials 938KB]

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