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  2021, Vol. 34 Issue (3): 275-285    DOI: 10.16451/j.cnki.issn1003-6059.202103009
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Calligraphic Chinese Characters Generation Based on Generative Adversarial Networks with Structural Constraint
YU Shushi1, ZHAO Jieyu1,2, YE Xulun1, TANG Chen1, ZHENG Yang1
1. Faculty of Electrical Engineering and Computer Science, Ning-bo University,Ningbo 315211
2. Mobile Network Application Technology Key Laboratory of Zhe-jiang Province, Ningbo 315211

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Abstract  

A large amount of prior composition information of Chinese characters is required for the generation of calligraphic Chinese characters. Moreover, the previous data collection is demanding work, and the scalability of the research results is easily affected. To solve this problem, a method of Chinese calligraphy characters generation based on structure constraint using conditional stack generative adversarial networks is proposed. The Chinese character handwriting extracted directly from the source Chinese character image is considered as the structure constraint condition. High-quality calligraphic Chinese characters are generated by the condition stack generative adversarial network model. A semi-supervised learning method based on pseudo target samples is proposed for the dataset lacking of calligraphic Chinese characters. Furthermore, the unseen calligraphic Chinese characters during training are generated as well. Experiments show the proposed method can generate higher-quality calligraphy Chinese characters under the premise of using a few samples of a specific style of calligraphic Chinese character dataset.

Key wordsCalligraphic Chinese Characters Generation      Generative Adversarial Network      Structural Constraint      Semi-Supervised Learning      Pseudo Target Sample     
Received: 26 November 2020     
ZTFLH: TP 391  
Fund:

National Natural Science Foundation of China(No.62071260,62006131)

Corresponding Authors: ZHAO Jieyu, Ph.D., professor. His research interests include computational intelligence, pattern recognition and natural human-computer interaction.   
About author:: YU Shushi, master student. Her research interests include generative adversarial networks and pattern recognition.YE Xulun, Ph.D., lecturer. His research interests include Bayesian learning and convex optimization.TANG Chen, master student. His research interests include graph neural networks and pattern recognition.ZHENG Yang, master student. His research interests include three dimensional con-volutional networks and pattern recognition.
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YU Shushi
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Cite this article:   
YU Shushi,ZHAO Jieyu,YE Xulun等. Calligraphic Chinese Characters Generation Based on Generative Adversarial Networks with Structural Constraint[J]. , 2021, 34(3): 275-285.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202103009      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2021/V34/I3/275
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