Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks

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