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  2020, Vol. 33 Issue (11): 959-971    DOI: 10.16451/j.cnki.issn1003-6059.202011001
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Gradient Controlled and Discriminative Features Guided Image-to-Image Translation Method Towards Realistic Portrait Illustrations
SHI Rongxiao1, YE Dongyi1, CHEN Zhaojiong1
1. College of Mathematics and Computer Science,Fuzhou University,Fuzhou 350108

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Abstract  

Without considering the preservation of facial recognition characteristics,the existing unsupervised image-to-image translation methods often suffer from face distortion and facial structure collapse.Consequently,it is difficult to identify the personal information after translation.To tackle this issue,gradient controlled and discriminative features guided image-to-image translation method towards realistic portrait illustrations is proposed based on cycle-consistent generative adversarial network(CycleGAN).Masked residual long connections are introduced by the proposed method to avoid reusing redundant features and image gradient information consistency is considered as a constraint to preserve facial recognition characteristics.In addition,a discriminative feature guided information-shared training mechanism is devised and thus generators are capable of capturing discriminative features of target images,like the discriminators.Moreover,patch-level discriminators are extended to multi-awareness discriminators to obtain more discriminative information.Experimental results show that the proposed method preserves facial recognition characteristics well in the translated illustrations and outperforms the existing unsupervised image-to-image translation methods in visual effect of illustrations.

Key wordsPortrait Illustration      Image-to-Image Translation      Cycle-Consistent Generative Adversarial Network(CycleGAN)      Image Gradient Consistency      Discriminative Feature     
Received: 13 August 2020     
ZTFLH: TP391.41  
Corresponding Authors: YE Dongyi,Ph.D.,professor.His research interests include computational intelligence and data mining.   
About author:: SHI Rongxiao,master student.His research interests include intelligent image processing;CHEN Zhaojiong,master,professor.Her research interests include intelligent image processing and computational intelligence.
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SHI Rongxiao
YE Dongyi
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Cite this article:   
SHI Rongxiao,YE Dongyi,CHEN Zhaojiong. Gradient Controlled and Discriminative Features Guided Image-to-Image Translation Method Towards Realistic Portrait Illustrations[J]. , 2020, 33(11): 959-971.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202011001      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2020/V33/I11/959
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