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Paper Abstract and Keywords
Presentation 2019-03-12 14:00
GAN Framework of Fitting Preference Distribution of "Kawaii"
Wu Shuangmei, Xie Haoran, Miyata Kazunori (JAIST)
Abstract (in Japanese) (See Japanese page) 
(in English) To study male characters reflecting user's preferences in the generation results is a challenging task. In this work, we propose a "kawaii" image generation framework of male animation character faces, which can adapt to Generative Adversarial Network (GAN) frameworks and fit user’s preferences. We present a dataset for the training of the proposed framework. We execute an evaluation experiment to verify the effectiveness of this framework. As a result, our proposed framework is effective, and the generation results of GAN with this framework are more fitted to the user's preference than before.
Keyword (in Japanese) (See Japanese page) 
(in English) GAN / User's Preferences / Generation / Animation Characters / / / /  
Reference Info. ITE Tech. Rep., vol. 43, no. 9, AIT2019-135, pp. 301-304, March 2019.
Paper #  
Date of Issue 2019-03-05 (AIT) 
ISSN Print edition: ISSN 1342-6893  Online edition: ISSN 2424-1970
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Conference Information
Committee AIT IIEEJ AS CG-ARTS  
Conference Date 2019-03-12 - 2019-03-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Waseda Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Expressive Japan 2019 
Paper Information
Registration To AS 
Conference Code 2019-03-AIT-IIEEJ-AS-ARTS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) GAN Framework of Fitting Preference Distribution of "Kawaii" 
Sub Title (in English)  
Keyword(1) GAN  
Keyword(2) User's Preferences  
Keyword(3) Generation  
Keyword(4) Animation Characters  
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1st Author's Name Wu Shuangmei  
1st Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
2nd Author's Name Xie Haoran  
2nd Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
3rd Author's Name Miyata Kazunori  
3rd Author's Affiliation Japan Advanced Institute of Science and Technology (JAIST)
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Speaker
Date Time 2019-03-12 14:00:00 
Presentation Time 135 
Registration for AS 
Paper # ITE-AIT2019-135 
Volume (vol) ITE-43 
Number (no) no.9 
Page pp.301-304 
#Pages ITE-4 
Date of Issue ITE-AIT-2019-03-05 


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