郭远同学论文《Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks》被Eurographics 2018录用为Oral 4页短文！
本论文介绍了一种基于流形学习和深度对抗网络的中文字库生成方法。
Eurographics（欧洲图形学会议）是计算机图形学领域国际顶级会议之一。
郭远同学是本论文第一作者，现为实验室二年级硕士研究生。
Y. Guo, Z. Lian*, Y. Tang, J. Xiao. Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks. Eurographics 2018 (accepted as a short oral paper)
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.