Paper Abstract and Keywords |
Presentation |
2022-03-11 14:15
Precise Affordance Annotation for Egocentric Action Video Datasets Zecheng Yu, Yifei Huang, Ryosuke Furuta, Yusuke Goutsu, Yoichi Sato (Univ. of Tokyo) PRMU2021-81 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Object affordance has attracted a growing interest in computer vision. It is an important concept that builds a bridge between human ability and object property, and provides fine-grained information for other tasks like activity forecasting, scene understanding, etc. Although affordance is investigated in many previous works, existing affordance datasets failed to distinguish affordance from other concepts like action and function. In this paper, We propose an efficient affordance annotation scheme for egocentric action video datasets to address this issue, which gives a clear and accurate definition of affordance. The scheme was applied to two large-scale egocentric video datasets: EPIC-KITCHENS and HOMAGE, and tested with various benchmark tasks. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
affordance / egocentric / dataset / annotation / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 427, PRMU2021-81, pp. 133-138, March 2022. |
Paper # |
PRMU2021-81 |
Date of Issue |
2022-03-03 (PRMU) |
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) |
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PRMU2021-81 |
Conference Information |
Committee |
PRMU IPSJ-CVIM |
Conference Date |
2022-03-10 - 2022-03-11 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Differentiable rendering |
Paper Information |
Registration To |
PRMU |
Conference Code |
2022-03-PRMU-CVIM |
Language |
English (Japanese title is available) |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Precise Affordance Annotation for Egocentric Action Video Datasets |
Sub Title (in English) |
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affordance |
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egocentric |
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annotation |
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1st Author's Name |
Zecheng Yu |
1st Author's Affiliation |
University of Tokyo (Univ. of Tokyo) |
2nd Author's Name |
Yifei Huang |
2nd Author's Affiliation |
University of Tokyo (Univ. of Tokyo) |
3rd Author's Name |
Ryosuke Furuta |
3rd Author's Affiliation |
University of Tokyo (Univ. of Tokyo) |
4th Author's Name |
Yusuke Goutsu |
4th Author's Affiliation |
University of Tokyo (Univ. of Tokyo) |
5th Author's Name |
Yoichi Sato |
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University of Tokyo (Univ. of Tokyo) |
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Speaker |
Author-1 |
Date Time |
2022-03-11 14:15:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2021-81 |
Volume (vol) |
vol.121 |
Number (no) |
no.427 |
Page |
pp.133-138 |
#Pages |
6 |
Date of Issue |
2022-03-03 (PRMU) |
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