An improved generative adversarial network for Chinese font generation

Suidong Qu; Gang Wang; Qinyu Que

doi:10.1117/12.2636411

6 May 2022 An improved generative adversarial network for Chinese font generation

Suidong Qu, Gang Wang, Qinyu Que

Proceedings Volume 12176, International Conference on Algorithms, Microchips and Network Applications; 121761U (2022) https://doi.org/10.1117/12.2636411
Event: International Conference on Algorithms, Microchips, and Network Applications 2022, 2022, Zhuhai, China

Abstract

Since drawing a complete set of high-quality Chinese calligraphy fonts by hand is time-consuming and labor-intensive, in order to realize the automatic drawing of Chinese calligraphy fonts, this paper proposes an encoder-decoder network model based on residual structure. The model realizes the automatic generation of Chinese calligraphy fonts through the adversarial training of the generator and the discriminator. Experiments show that our method can not only generate realistic calligraphy fonts, but also has the ability to generate a complete font library.

Citation Download Citation

Suidong Qu, Gang Wang, and Qinyu Que "An improved generative adversarial network for Chinese font generation", Proc. SPIE 12176, International Conference on Algorithms, Microchips and Network Applications, 121761U (6 May 2022); https://doi.org/10.1117/12.2636411

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