Paper Abstract and Keywords |
Presentation |
2022-03-08 14:45
Evaluation of Data Augmentation Methods Considering Occlusion Region for 3D Point Cloud Classification Shiori Maki, Kenji Kanai, Shota Hirose, Heming Sun, Jiro Katto (Waseda Univ.) SeMI2021-91 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, research of point cloud classification using deep learning has been improved. In this paper, we propose a data augmentation method for building a robust model against occlusions. The proposed model is inspired by the 2D data augmentation methods, such as random erasing and cutout methods. Through the performance evaluations, we verify that the proposed method can contribute to improvement of classification accuracy even if a part of point cloud is lacked due to the occlusion. In addition, we also verify availability of the proposed method against real data and adversarial data that intentionally drops important points. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Point Cloud / Deep Learning / Data Augmentation / Digital Twin / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 411, SeMI2021-91, pp. 47-52, March 2022. |
Paper # |
SeMI2021-91 |
Date of Issue |
2022-02-28 (SeMI) |
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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SeMI2021-91 |
Conference Information |
Committee |
SeMI IPSJ-MBL IPSJ-UBI |
Conference Date |
2022-03-07 - 2022-03-08 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
SeMI |
Conference Code |
2022-03-SeMI-MBL-UBI |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Evaluation of Data Augmentation Methods Considering Occlusion Region for 3D Point Cloud Classification |
Sub Title (in English) |
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Keyword(1) |
Point Cloud |
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Deep Learning |
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Data Augmentation |
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Digital Twin |
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1st Author's Name |
Shiori Maki |
1st Author's Affiliation |
Waseda University (Waseda Univ.) |
2nd Author's Name |
Kenji Kanai |
2nd Author's Affiliation |
Waseda University (Waseda Univ.) |
3rd Author's Name |
Shota Hirose |
3rd Author's Affiliation |
Waseda University (Waseda Univ.) |
4th Author's Name |
Heming Sun |
4th Author's Affiliation |
Waseda University (Waseda Univ.) |
5th Author's Name |
Jiro Katto |
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Waseda University (Waseda Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-03-08 14:45:00 |
Presentation Time |
25 minutes |
Registration for |
SeMI |
Paper # |
SeMI2021-91 |
Volume (vol) |
vol.121 |
Number (no) |
no.411 |
Page |
pp.47-52 |
#Pages |
6 |
Date of Issue |
2022-02-28 (SeMI) |
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