Paper Abstract and Keywords |
Presentation |
2018-03-19 15:35
Accuracy Improvement of Fashon Style Classification by Appropriate Training Data and Estimation of Human Regions Takeshi Nakajima, Takuro Oki, Ryusuke Miyamoto (Meiji Univ.) EA2017-137 SIP2017-146 SP2017-120 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Fashion style estimation from an input image where a human wearing clothes exists is a challenging task in the field of image recognition. This paper tries to improve the classification accuracy of fashion style estimation by the following two approaches: construction of an appropriate data set with style labels and preprocessing with semantic segmentation to reduce the influence of background regions. The data set constructed in this work improved the classification accuracy of the Hipster Wars data set to about 78.8%. When the semantic segmentation based on PSPNet was applied with our data set, the classification accuracy was improved to about 80.9% that is currently the best accuracy in the world. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Fashion style estimation / large-scale data set / deep neural network / semantic segmentation / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 516, SIP2017-146, pp. 197-202, March 2018. |
Paper # |
SIP2017-146 |
Date of Issue |
2018-03-12 (EA, SIP, SP) |
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 |
EA2017-137 SIP2017-146 SP2017-120 |
Conference Information |
Committee |
SIP EA SP MI |
Conference Date |
2018-03-19 - 2018-03-20 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
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Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] |
Paper Information |
Registration To |
SIP |
Conference Code |
2018-03-SIP-EA-SP-MI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Accuracy Improvement of Fashon Style Classification by Appropriate Training Data and Estimation of Human Regions |
Sub Title (in English) |
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Keyword(1) |
Fashion style estimation |
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large-scale data set |
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deep neural network |
Keyword(4) |
semantic segmentation |
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1st Author's Name |
Takeshi Nakajima |
1st Author's Affiliation |
Meiji University (Meiji Univ.) |
2nd Author's Name |
Takuro Oki |
2nd Author's Affiliation |
Meiji University (Meiji Univ.) |
3rd Author's Name |
Ryusuke Miyamoto |
3rd Author's Affiliation |
Meiji University (Meiji Univ.) |
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Speaker |
Author-1 |
Date Time |
2018-03-19 15:35:00 |
Presentation Time |
25 minutes |
Registration for |
SIP |
Paper # |
EA2017-137, SIP2017-146, SP2017-120 |
Volume (vol) |
vol.117 |
Number (no) |
no.515(EA), no.516(SIP), no.517(SP) |
Page |
pp.197-202 |
#Pages |
6 |
Date of Issue |
2018-03-12 (EA, SIP, SP) |
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