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Paper Abstract and Keywords
Presentation 2025-02-19 11:40
Performance Enhancement Free Viewpoint Image Methods Using for Deep-Learning Super-Resolution Techniques
Kaito Houjho, Ren Nakasato, Terumasa Aoki (TUT) ITS2024-84 IE2024-76
Abstract (in Japanese) (See Japanese page) 
(in English) Free viewpoint image is a technology that allows the viewer to see in all directions. Recently, free viewpoint images have attracted much attention. Since these methods estimate the ray space from image pixels, the input image greatly affects the generation accuracy. To generate free viewpoint images, high-resolution cameras are usually required. However, many drones and robots use low-resolution cameras to minimize size and weight. This limitation in resolution makes it difficult to produce high-quality free viewpoint images with such devices. On the other hand, to generate highly accurate free viewpoint images from low-resolution images, free viewpoint image generation techniques could be combined with super-resolution techniques. However, the optimal way to combine free viewpoint images and super-resolution methods has not been clarified.
In this paper, we focus on enhancing the resolution of input images and improving the accuracy of free-viewpoint images using a deep learning-based super-resolution method. It also reveals how to combine free viewpoint image generation and super-resolution techniques to produce high-quality free viewpoint images from low-resolution images.
Keyword (in Japanese) (See Japanese page) 
(in English) Novel View Synthesis / Free Viewpoint Image Generation / Deep Learning / Super Resolution / Radiance Fields / / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 373, IE2024-76, pp. 188-193, Feb. 2025.
Paper # IE2024-76 
Date of Issue 2025-02-11 (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 ITS2024-84 IE2024-76

Conference Information
Committee ITS IE ITE-MMS ITE-ME ITE-AIT ITE-SIP  
Conference Date 2025-02-18 - 2025-02-19 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2025-02-ITS-IE-MMS-ME-AIT-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Enhancement Free Viewpoint Image Methods Using for Deep-Learning Super-Resolution Techniques 
Sub Title (in English)  
Keyword(1) Novel View Synthesis  
Keyword(2) Free Viewpoint Image Generation  
Keyword(3) Deep Learning  
Keyword(4) Super Resolution  
Keyword(5) Radiance Fields  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Kaito Houjho  
1st Author's Affiliation Tokyo University of Technology (TUT)
2nd Author's Name Ren Nakasato  
2nd Author's Affiliation Tokyo University of Technology (TUT)
3rd Author's Name Terumasa Aoki  
3rd Author's Affiliation Tokyo University of Technology (TUT)
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Speaker Author-1 
Date Time 2025-02-19 11:40:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2024-84, IE2024-76 
Volume (vol) vol.124 
Number (no) no.372(ITS), no.373(IE) 
Page pp.188-193 
#Pages 6 
Date of Issue 2025-02-11 (ITS, IE) 

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