GlyphGAN: Style-Consistent Font Generation Based on Generative Adversarial Networks

29 May 2019Hideaki HayashiKohtaro AbeSeiichi Uchida

In this paper, we propose GlyphGAN: style-consistent font generation based on generative adversarial networks (GANs). GANs are a framework for learning a generative model using a system of two neural networks competing with each other... (read more)

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