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Paper Abstract and Keywords
Presentation 2024-12-22 09:30
**
Youhei Ueno, Masataka Seo (Osaka Institute of Technology)
Abstract (in Japanese) (See Japanese page) 
(in English) There are two problems with video generation using deep generative models. The first problem is that objects moving between frames tend to be blurred. The second problem is that areas that do not change between frames are generated with changes. To solve these problems, we aim to improve generation accuracy by adding the edge features error and the optical flow error calculated from target data and generated data. In addition, Video Swin Transformer is used as a generator to capture the correlation of features across the entire video, including space and time, to generate high-definition video.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep learning / Video conversion / / / / / /  
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Conference Information
Committee KANSAI  
Conference Date 2024-12-22 - 2024-12-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Osaka Metropolitan University, I-site Namba 
Topics (in Japanese) (See Japanese page) 
Topics (in English) The Institute of Image Information and Television Engineers, Kansai chapter, Workshop for young researchers 
Paper Information
Registration To KANSAI 
Conference Code 2024-12-KANSAI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) ** 
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Keyword(1) Deep learning  
Keyword(2) Video conversion  
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1st Author's Name Youhei Ueno  
1st Author's Affiliation Osaka Institute of Technology (Osaka Institute of Technology)
2nd Author's Name Masataka Seo  
2nd Author's Affiliation Osaka Institute of Technology (Osaka Institute of Technology)
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Speaker Author-1 
Date Time 2024-12-22 09:30:00 
Presentation Time 15 minutes 
Registration for KANSAI 
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