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| Presentation | 2023-05-19 09:20 Learning static NeRF representations from video using 2D segmentation masks Takashi Otonari (Tokyo Univ.), Satoshi Ikehata (NII), Kiyoharu Aizawa (Tokyo Univ.)  PRMU2023-7 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we tackle the problem of extracting static backgrounds from videos containing moving objects, such as people and cars. RobustNeRF, the current state-of-the-art method for extracting static backgrounds, often struggles to separate high-frequency static backgrounds from dynamic foregrounds in real-world scenes. We introduce Test Time Augmentation, and our experiments demonstrate that the additional segmentation masks effectively remove dynamic foregrounds in scenes with high-frequency static backgrounds, an area where existing methods have faced difficulties. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | neural radiance field / NeRF / novel view synthesis / scene decomposition / semantic segmentation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 30, PRMU2023-7, pp. 33-38, May 2023. | |
| Paper # | PRMU2023-7 | |
| Date of Issue | 2023-05-11 (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) | |
| Download PDF | PRMU2023-7 |
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| Conference Information | |
| Committee | PRMU IPSJ-CVIM |
| Conference Date | 2023-05-18 - 2023-05-19 |
| 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 | 2023-05-PRMU-CVIM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Learning static NeRF representations from video using 2D segmentation masks |
| Sub Title (in English) | |
| Keyword(1) | neural radiance field |
| Keyword(2) | NeRF |
| Keyword(3) | novel view synthesis |
| Keyword(4) | scene decomposition |
| Keyword(5) | semantic segmentation |
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| 1st Author's Name | Takashi Otonari |
| 1st Author's Affiliation | The University of Tokyo (Tokyo Univ.) |
| 2nd Author's Name | Satoshi Ikehata |
| 2nd Author's Affiliation | National Institute of Informatics (NII) |
| 3rd Author's Name | Kiyoharu Aizawa |
| 3rd Author's Affiliation | The University of Tokyo (Tokyo Univ.) |
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| Speaker | Author-1 |
| Date Time | 2023-05-19 09:20:00 |
| Presentation Time | 15 minutes |
| Registration for | PRMU |
| Paper # | PRMU2023-7 |
| Volume (vol) | vol.123 |
| Number (no) | no.30 |
| Page | pp.33-38 |
| #Pages | 6 |
| Date of Issue | 2023-05-11 (PRMU) |
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