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Paper Abstract and Keywords
Presentation 2023-07-01 10:45
A Study on generating First-Person Video in moving daily space using variational auto encoders
Xu Chenfei (Osaka Univ.), Okadome Yuya (TUS), Ishiguro Hiroshi (Osaka Univ.), Nakamura Yutaka (RIKEN) NC2023-24 IBISML2023-24
Abstract (in Japanese) (See Japanese page) 
(in English) Current researches on robot navigation mainly emphasize on responsive behaviors, but it usually presents insufficient intelligence if we want robots be better integrated into human society. To cope with this issue, we are tackling to model the change of the state including other person’s motion by using a deep generative model. In terms of Variational Autoencoders, different factors like hyperparameters, the dimensions of latent space and loss function can directly influence the generation quality. However, the concrete effect of these factors still needs to be studied. Thus, this paper works out an investigation which goes deep in this problem. In particular, we built a VAE based generative model with 3D ConvNet for video reconstruction task. Then we have summarized and compared models’ performances with various combinations of influencing factors and discovered their disentangled representation. A Variational Autoencoder with Arbitrary Conditioning(VAEAC) based prediction model was also evaluated. Our results demonstrate how the performance of generative models was changed to offer a good instance for video prediction problem.
Keyword (in Japanese) (See Japanese page) 
(in English) Variational Autoencoder / Variational Autoencoder with Arbitrary Conditioning / disentangled representation / video generation / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 90, NC2023-24, pp. 153-158, June 2023.
Paper # NC2023-24 
Date of Issue 2023-06-22 (NC, IBISML) 
ISSN Online edition: ISSN 2432-6380
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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 NC2023-24 IBISML2023-24

Conference Information
Committee NC IBISML IPSJ-BIO IPSJ-MPS  
Conference Date 2023-06-29 - 2023-07-01 
Place (in Japanese) (See Japanese page) 
Place (in English) OIST Conference Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2023-06-NC-IBISML-BIO-MPS 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on generating First-Person Video in moving daily space using variational auto encoders 
Sub Title (in English)  
Keyword(1) Variational Autoencoder  
Keyword(2) Variational Autoencoder with Arbitrary Conditioning  
Keyword(3) disentangled representation  
Keyword(4) video generation  
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1st Author's Name Xu Chenfei  
1st Author's Affiliation Osaka Univeristy (Osaka Univ.)
2nd Author's Name Okadome Yuya  
2nd Author's Affiliation Tokyo University of Science (TUS)
3rd Author's Name Ishiguro Hiroshi  
3rd Author's Affiliation Osaka Univeristy (Osaka Univ.)
4th Author's Name Nakamura Yutaka  
4th Author's Affiliation RIKEN (RIKEN)
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Speaker Author-1 
Date Time 2023-07-01 10:45:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2023-24, IBISML2023-24 
Volume (vol) vol.123 
Number (no) no.90(NC), no.91(IBISML) 
Page pp.153-158 
#Pages
Date of Issue 2023-06-22 (NC, IBISML) 


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