Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks

Guo, Yuan; Lian, Zhouhui; Tang, Yingmin; Xiao, Jianguo

Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks

Files

061-064.pdf (1.96 MB)

Date

2018

Authors

Guo, Yuan
Lian, Zhouhui
Tang, Yingmin
Xiao, Jianguo

Publisher

The Eurographics Association

Abstract

The design of fonts, especially Chinese fonts, is known as a tough task that requires considerable time and professional skills. In this paper, we propose a method to easily generate Chinese font libraries in new styles based on manifold learning and adversarial networks. Starting from a number of existing fonts that cover various styles, we firstly use convolutional neural networks to obtain the representation features of these fonts, and then build a font manifold via non-linear mapping. Using the font manifold, we can interpolate and move between those existing fonts to get new font features, which are then fed into a generative network learned via adversarial training to generate the whole new font libraries. Experimental results demonstrate that high-quality Chinese fonts in various new styles against existing ones can be efficiently generated using our method.

        @inproceedings{10.2312:egs.20181045
,
booktitle = {EG 2018 - Short Papers
},
editor = {Diamanti, Olga and Vaxman, Amir
},
title = {{Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks
}},
author = {Guo, Yuan and 
Lian, Zhouhui and 
Tang, Yingmin and 
Xiao, Jianguo
},
year = {2018
},
publisher = {The Eurographics Association
},
ISSN = {1017-4656
},
ISBN = {},
DOI = {10.2312/egs.20181045
}
}