SGCE-Font: Skeleton Guided Channel Expansion for Chinese Font Generation

التفاصيل البيبلوغرافية
العنوان: SGCE-Font: Skeleton Guided Channel Expansion for Chinese Font Generation
المؤلفون: Zhou, Jie, Wang, Yefei, Yuan, Yiyang, Huang, Qing, Zeng, Jinshan
سنة النشر: 2022
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
الوصف: The automatic generation of Chinese fonts is an important problem involved in many applications. The predominated methods for the Chinese font generation are based on the deep generative models, especially the generative adversarial networks (GANs). However, existing GAN-based methods (say, CycleGAN) for the Chinese font generation usually suffer from the mode collapse issue, mainly due to the lack of effective guidance information. This paper proposes a novel information guidance module called the skeleton guided channel expansion (SGCE) module for the Chinese font generation through integrating the skeleton information into the generator with the channel expansion way, motivated by the observation that the skeleton embodies both local and global structure information of Chinese characters. We conduct extensive experiments to show the effectiveness of the proposed module. Numerical results show that the mode collapse issue suffered by the known CycleGAN can be effectively alleviated by equipping with the proposed SGCE module, and the CycleGAN equipped with SGCE outperforms the state-of-the-art models in terms of four important evaluation metrics and visualization quality. Besides CycleGAN, we also show that the suggested SGCE module can be adapted to other models for Chinese font generation as a plug-and-play module to further improve their performance.
Comment: 12 pages, 9 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2211.14475
رقم الأكسشن: edsarx.2211.14475
قاعدة البيانات: arXiv