English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The automatic generation of Chinese fonts is an important problem involved inmany applications. The predominated methods for the Chinese font generation arebased on the deep generative models, especially the generative adversarialnetworks (GANs). However, existing GAN-based methods (say, CycleGAN) for theChinese font generation usually suffer from the mode collapse issue, mainly dueto the lack of effective guidance information. This paper proposes a novelinformation guidance module called the skeleton guided channel expansion (SGCE)module for the Chinese font generation through integrating the skeletoninformation into the generator with the channel expansion way, motivated by theobservation that the skeleton embodies both local and global structureinformation of Chinese characters. We conduct extensive experiments to show theeffectiveness of the proposed module. Numerical results show that the modecollapse issue suffered by the known CycleGAN can be effectively alleviated byequipping with the proposed SGCE module, and the CycleGAN equipped with SGCEoutperforms the state-of-the-art models in terms of four important evaluationmetrics and visualization quality. Besides CycleGAN, we also show that thesuggested SGCE module can be adapted to other models for Chinese fontgeneration as a plug-and-play module to further improve their performance.

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