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Paper Abstract and Keywords
Presentation 2026-01-30 10:30
Time-Evolving Appearance Synthesis via Image-Derived Scene Descriptions with Locally Controllable Latent Diffusion
Koki Fukushima (Univ. Tsukuba), Guoqing Hao (Aoyama Gakuin Univ.), Satoshi Iizuka, Kazuhiro Fukui (Univ. Tsukuba) PRMU2025-32
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a diffusion-based framework that synthesizes continuously time-evolving weathering effects from a single image. Existing physics-based and diffusion-based editing methods are limited to specific degradation types, require manual masks and prompt engineering, often distort scene layout and object identity, and offer poor continuous control over the degree of weathering. Our method uses a vision–language model to automatically extract a scene description and a weathering description from the input image, and personalizes a latent diffusion model to reconstruct the original image from the scene description and image edges. Given the personalized model, we condition it on the weathering description and image edges and nonlinearly control the noise level in the reverse diffusion process, enabling continuous synthesis of time-evolving appearances, including both progression and regression, while preserving object identity.
Keyword (in Japanese) (See Japanese page) 
(in English) latent diffusion models / image-based weathering / vision-language models / image editing / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 348, PRMU2025-32, pp. 43-48, Jan. 2026.
Paper # PRMU2025-32 
Date of Issue 2026-01-22 (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 PRMU2025-32

Conference Information
Committee PRMU IPSJ-CVIM VRSJ-SIG-MR MVE  
Conference Date 2026-01-29 - 2026-01-30 
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 2026-01-PRMU-CVIM-SIG-MR-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Time-Evolving Appearance Synthesis via Image-Derived Scene Descriptions with Locally Controllable Latent Diffusion 
Sub Title (in English)  
Keyword(1) latent diffusion models  
Keyword(2) image-based weathering  
Keyword(3) vision-language models  
Keyword(4) image editing  
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1st Author's Name Koki Fukushima  
1st Author's Affiliation University of Tsukuba (Univ. Tsukuba)
2nd Author's Name Guoqing Hao  
2nd Author's Affiliation Aoyama Gakuin University (Aoyama Gakuin Univ.)
3rd Author's Name Satoshi Iizuka  
3rd Author's Affiliation University of Tsukuba (Univ. Tsukuba)
4th Author's Name Kazuhiro Fukui  
4th Author's Affiliation University of Tsukuba (Univ. Tsukuba)
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Speaker Author-1 
Date Time 2026-01-30 10:30:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2025-32 
Volume (vol) vol.125 
Number (no) no.348 
Page pp.43-48 
#Pages 6 
Date of Issue 2026-01-22 (PRMU) 

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