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Paper Abstract and Keywords
Presentation 2017-06-02 15:00
Quantitative evaluation method of the reality of CG images using deep learning
Masaaki Sato, Masataka Imura (Kwansei Gakuin Univ.) MVE2017-10
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 / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 73, MVE2017-10, pp. 173-176, June 2017.
Paper # MVE2017-10 
Date of Issue 2017-05-25 (MVE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF MVE2017-10

Conference Information
Committee MVE ITE-HI  
Conference Date 2017-06-01 - 2017-06-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Univ. of Tokyo 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To 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 15:00:00 
Presentation Time 20 minutes 
Registration for MVE 
Paper # MVE2017-10 
Volume (vol) vol.117 
Number (no) no.73 
Page pp.173-176 
#Pages
Date of Issue 2017-05-25 (MVE) 


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