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| Presentation | 2022-02-22 10:00 Pretext-Contrastive Learning for Self-Supervised Video Feature Learning Li Tao (UTokyo), Xueting Wang (CyberAgent, Inc.), Toshihiko Yamasaki (UTokyo)  ITS2021-43 IE2021-52 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Recently, pretext task-based methods are proposed one after another in self-supervised video feature learning. Contrastive learning-based methods also yield good performance. In this paper, we propose a framework which can easily combine pretext task-based method and contrastive learning-based method together. With some data strategies, huge improvements over the baselines can be achieved, indicating that a joint optimization framework can boost both pretext task and contrastive learning. We also show some analyses towards the potential mechanism behind it. It is convenient to treat our training framework as a standard training strategy and apply it to many other works in self-supervised video feature learning. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | video feature / self-supervised learning / pretext task / contrastive learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 374, IE2021-52, pp. 109-114, Feb. 2022. | |
| Paper # | IE2021-52 | |
| Date of Issue | 2022-02-14 (ITS, IE) | |
| 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 | ITS2021-43 IE2021-52 |
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| Conference Information | |
| Committee | IE ITS ITE-AIT ITE-ME ITE-MMS |
| Conference Date | 2022-02-21 - 2022-02-22 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Image Processing, etc. |
| Paper Information | |
| Registration To | IE |
| Conference Code | 2022-02-IE-ITS-AIT-ME-MMS |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Pretext-Contrastive Learning for Self-Supervised Video Feature Learning |
| Sub Title (in English) | |
| Keyword(1) | video feature |
| Keyword(2) | self-supervised learning |
| Keyword(3) | pretext task |
| Keyword(4) | contrastive learning |
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| 1st Author's Name | Li Tao |
| 1st Author's Affiliation | The University of Tokyo (UTokyo) |
| 2nd Author's Name | Xueting Wang |
| 2nd Author's Affiliation | CyberAgent, Inc. (CyberAgent, Inc.) |
| 3rd Author's Name | Toshihiko Yamasaki |
| 3rd Author's Affiliation | The University of Tokyo (UTokyo) |
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| Speaker | Author-1 |
| Date Time | 2022-02-22 10:00:00 |
| Presentation Time | 15 minutes |
| Registration for | IE |
| Paper # | ITS2021-43, IE2021-52 |
| Volume (vol) | vol.121 |
| Number (no) | no.373(ITS), no.374(IE) |
| Page | pp.109-114 |
| #Pages | 6 |
| Date of Issue | 2022-02-14 (ITS, IE) |
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