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Paper Abstract and Keywords
Presentation 2017-06-02 14:50
Quantitative evaluation method of the reality of CG images using deep learning
Masaaki Sato, Masataka Imura (Kwansei Gakuin Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) With the development of 3DCG technology, to express various objects and phenomena became possible. However, there is no method for quantitatively evaluating the reality of the generated CG image. On the other hand, in recent years, deep learning has been widely used to demonstrate image discrimination performance beyond human beings. In this paper, we propose a framework to realize quantitative evaluation of reality of CG image by utilizing deep learning that has high image discrimination ability and report implementation results using CNN.
Keyword (in Japanese) (See Japanese page) 
(in English) CG / Reality / Quantitative evaluation / Deep Learning / CNN / / /  
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Conference Information
Committee HI IEICE-MVE VRSJ  
Conference Date 2017-06-01 - 2017-06-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Yayoi Auditorium, Ichijo Hall / Annex 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IEICE-MVE 
Conference Code 2017-06-MVE-HI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Quantitative evaluation method of the reality of CG images using deep learning 
Sub Title (in English)  
Keyword(1) CG  
Keyword(2) Reality  
Keyword(3) Quantitative evaluation  
Keyword(4) Deep Learning  
Keyword(5) CNN  
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1st Author's Name Masaaki Sato  
1st Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
2nd Author's Name Masataka Imura  
2nd Author's Affiliation Kwansei Gakuin University (Kwansei Gakuin Univ.)
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Speaker Author-1 
Date Time 2017-06-02 14:50:00 
Presentation Time 20 minutes 
Registration for IEICE-MVE 
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Volume (vol) vol.41 
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