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| Paper Abstract and Keywords | ||
| Presentation | 2022-06-28 10:05 Learning Attribute Vector Fields in GAN Latent Space Takehiro Aoshima, Takashi Matsubara (Osaka Univ.)  NC2022-12 IBISML2022-12 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Generative Adversarial Networks (GANs) can generate a great variety of high-quality images. Despite their ability to generate images, semantic editing of GANs generated images is troublesome. To address this, recent studies proposed methods to discover semantically meaningful directions in GANs latent space. For semantic image editing, latent codes are manipulated along with discovered directions. However, these methods sometimes fail to discover such directions or cannot edit multiple attributes consistently. In this paper, we propose a method to learn semantic curvilinear coordinates in GANs latent space. The proposed method can discover a variety of semantic directions in GANs latent space and edit multiple attributes consistently. Experimental results on some pretrained GANs show that our methods can discover more disentangled semantic directions and edit images while conserving identity than a comparative method. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Image Editing / Generative Adversarial Networks / Curvilinear Coordinates / Normalizing Flows / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 90, IBISML2022-12, pp. 94-99, June 2022. | |
| Paper # | IBISML2022-12 | |
| Date of Issue | 2022-06-20 (NC, IBISML) | |
| 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 | NC2022-12 IBISML2022-12 |
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| Conference Information | |
| Committee | NC IBISML IPSJ-BIO IPSJ-MPS |
| Conference Date | 2022-06-27 - 2022-06-29 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2022-06-NC-IBISML-BIO-MPS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Learning Attribute Vector Fields in GAN Latent Space |
| Sub Title (in English) | |
| Keyword(1) | Image Editing |
| Keyword(2) | Generative Adversarial Networks |
| Keyword(3) | Curvilinear Coordinates |
| Keyword(4) | Normalizing Flows |
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| Keyword(8) | |
| 1st Author's Name | Takehiro Aoshima |
| 1st Author's Affiliation | Osaka University (Osaka Univ.) |
| 2nd Author's Name | Takashi Matsubara |
| 2nd Author's Affiliation | Osaka University (Osaka Univ.) |
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| Speaker | Author-1 |
| Date Time | 2022-06-28 10:05:00 |
| Presentation Time | 25 minutes |
| Registration for | IBISML |
| Paper # | NC2022-12, IBISML2022-12 |
| Volume (vol) | vol.122 |
| Number (no) | no.89(NC), no.90(IBISML) |
| Page | pp.94-99 |
| #Pages | 6 |
| Date of Issue | 2022-06-20 (NC, IBISML) |
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