NDLI: Learning one-to-many stylised Chinese character transformation and generation by generative adversarial networks

Content Provider	IET Digital Library
Author	Chen, Jiefu Ji, Yanli Chen, Hua Xu, Xing
Abstract	Owing to the complex structure of Chinese characters and the huge number of Chinese characters, it is very challenging and time consuming for artists to design a new font of Chinese characters. Therefore, the generation of Chinese characters and the transformation of font styles have become research hotspots. At present, most of the models on Chinese character transformation cannot generate multiple fonts, and they are not doing well in faking fonts. In this article, the authors propose a novel method of Chinese character fonts transformation and generation based on generative adversarial networks. The authors’ model is able to generate multiple fonts at once through font style-specifying mechanism and it can generate a new font at the same time if the authors combine the characteristics of existing fonts.
Starting Page	2680
Ending Page	2686
Page Count	7
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 14, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0009
Journal	IET Image Processing
Publisher Date	2019-06-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Character Sets Chinese Character Fonts Transformation Computer Vision And Image Processing Technique Document Image Processing Document Processing Technique Feature Extraction Font Style-specifying Mechanism Generative Adversarial Network Image Recognition Knowledge Engineering Technique Learning in AI Natural Language Processing Optical Character Recognition Stylised Chinese Character Transformation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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