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Paper Abstract and Keywords
Presentation 2017-10-12 09:30
An Effective De-noising Algorithm for Making A Large Celebrity Face Dataset with A High Purity
Zheng Ge, Quan Cui (Waseda Univ.), Rong Xu, Masahiro Imai (Datasection Inc.), Osamu Yoshie (Waseda Univ.) PRMU2017-67
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, face recognition has been greatly improved by the development of CNN such as DeepID, FaceNet, and so on. However, the performance of those trained models is not satisfactory when applied on Asian face recognition because those models are almost trained on western face datasets. In order to solve such a problem, we create a large Chinese celebrity face dataset, including 11,289 celebrities and 395,130 face images, and then we can make a fine tune on those trained models for Asian face recognition by our created Chinese celebrity dataset.
In this paper, we make a scheme to collect celebrity names and images from unstructured data by internet. Then we propose an effective de-noising algorithm to improve the quality of dataset, and the purity of our data can reach 97.7% from original 65.9% after the de-noising. Meanwhile, the de-noising operation on MS-Celeb-1M has been realized for evaluating the proposed method, and the purity of the tested fine part of MS-Celeb-1M has been improved from 73.0% to 98.7%. Therefore, the experiments on our created Chinese celebrity face dataset and MS-Celeb-1M indicate that the proposed de-noising algorithm has achieved excellent performance for improving the quality of dataset.
Keyword (in Japanese) (See Japanese page) 
(in English) CNN / Face dataset / Denoising Algorithm / / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 238, PRMU2017-67, pp. 25-30, Oct. 2017.
Paper # PRMU2017-67 
Date of Issue 2017-10-05 (PRMU) 
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)
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Conference Information
Committee PRMU  
Conference Date 2017-10-12 - 2017-10-13 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To PRMU 
Conference Code 2017-10-PRMU 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Effective De-noising Algorithm for Making A Large Celebrity Face Dataset with A High Purity 
Sub Title (in English)  
Keyword(1) CNN  
Keyword(2) Face dataset  
Keyword(3) Denoising Algorithm  
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1st Author's Name Zheng Ge  
1st Author's Affiliation Waseda University (Waseda Univ.)
2nd Author's Name Quan Cui  
2nd Author's Affiliation Waseda University (Waseda Univ.)
3rd Author's Name Rong Xu  
3rd Author's Affiliation Datasection (Datasection Inc.)
4th Author's Name Masahiro Imai  
4th Author's Affiliation Datasection (Datasection Inc.)
5th Author's Name Osamu Yoshie  
5th Author's Affiliation Waseda University (Waseda Univ.)
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Speaker Author-1 
Date Time 2017-10-12 09:30:00 
Presentation Time 30 minutes 
Registration for PRMU 
Paper # PRMU2017-67 
Volume (vol) vol.117 
Number (no) no.238 
Page pp.25-30 
#Pages 6 
Date of Issue 2017-10-05 (PRMU) 

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