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Paper Abstract and Keywords
Presentation 2021-09-17 14:30
Improving Mask Generation Accuracy Exploiting Optical Flow in Weakly Supervised Instance Segmentation
Jun Ikeda, Junichiro Mori (UTokyo) MVE2021-15
Abstract (in Japanese) (See Japanese page) 
(in English) Weakly supervised instance segmentation is important because it reduces the huge pixel-level annotation cost required to train models. One of the challenges in the weakly supervised approaches which rely on instance-level class labels and bounding boxes is to efficiently learn foreground features by separating the foreground from the background in the bounding box. However, existing approach often misrecognize the background area as the foreground due to the imperfect separation by the local color similarity. We focus on the observation that the foreground is likely to move differently from the backgound, and show that observing the difference in optical flow enable us to separate them in a different way than color. Then, we propose considering the optical flow similarity in addition to the color similarity to generate the pseudo labels for mask head training. Moreover, we demonstrate that our model outperforms the existing method on YouTube-VIS and that our model improves the misrecognition.
Keyword (in Japanese) (See Japanese page) 
(in English) instance segmentation / weakly supervised learning / optical flow / video / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 179, MVE2021-15, pp. 38-43, Sept. 2021.
Paper # MVE2021-15 
Date of Issue 2021-09-10 (MVE) 
ISSN 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 MVE2021-15

Conference Information
Committee MVE  
Conference Date 2021-09-17 - 2021-09-18 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MVE 
Conference Code 2021-09-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improving Mask Generation Accuracy Exploiting Optical Flow in Weakly Supervised Instance Segmentation 
Sub Title (in English)  
Keyword(1) instance segmentation  
Keyword(2) weakly supervised learning  
Keyword(3) optical flow  
Keyword(4) video  
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1st Author's Name Jun Ikeda  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Junichiro Mori  
2nd Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2021-09-17 14:30:00 
Presentation Time 30 minutes 
Registration for MVE 
Paper # MVE2021-15 
Volume (vol) vol.121 
Number (no) no.179 
Page pp.38-43 
#Pages 6 
Date of Issue 2021-09-10 (MVE) 

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