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Paper Abstract and Keywords
Presentation 2026-03-27 14:00
A fundamental study on real-time action detection methods for game characters
Mahiro Tokumasu, Itsuki Okuma (Shizuoka Univ.), Kazuki Abe, Ryota Sakiyama, Naohiro Nomura (CAPCOM), Tetsushi Ohki (Shizuoka Univ./RIKEN AIP) BioX2025-101 CNR2025-20
Abstract (in Japanese) (See Japanese page) 
(in English) Existing gameplay AI mostly aims to clear games, and few frameworks independently assess situation understanding—a key prerequisite for decision making.To support this, we formulate a spatio-temporal action detection (STAD) task that predicts character regions and action labels for each frame.By fine-tuning the lightweight STAD model YOWOv3 on a proprietary dataset and adding temporal soft labels to smooth action transitions, we achieve over 0.90 mAP@0.50 $geq$ 0.90 with 50 ms inference latency at 30 FPS, demonstrating the practicality of STAD for gameplay AI agents.
Keyword (in Japanese) (See Japanese page) 
(in English) Gameplay AI Agents / Spatio-Temporal Action Detection / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 426, BioX2025-101, pp. 38-43, March 2026.
Paper # BioX2025-101 
Date of Issue 2026-03-19 (BioX, CNR) 
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 BioX2025-101 CNR2025-20

Conference Information
Committee CNR BioX  
Conference Date 2026-03-26 - 2026-03-27 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To BioX 
Conference Code 2026-03-CNR-BioX 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A fundamental study on real-time action detection methods for game characters 
Sub Title (in English)  
Keyword(1) Gameplay AI Agents  
Keyword(2) Spatio-Temporal Action Detection  
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1st Author's Name Mahiro Tokumasu  
1st Author's Affiliation Shizuoka University (Shizuoka Univ.)
2nd Author's Name Itsuki Okuma  
2nd Author's Affiliation Shizuoka University (Shizuoka Univ.)
3rd Author's Name Kazuki Abe  
3rd Author's Affiliation CAPCOM CO., LTD. (CAPCOM)
4th Author's Name Ryota Sakiyama  
4th Author's Affiliation CAPCOM CO., LTD. (CAPCOM)
5th Author's Name Naohiro Nomura  
5th Author's Affiliation CAPCOM CO., LTD. (CAPCOM)
6th Author's Name Tetsushi Ohki  
6th Author's Affiliation Shizuoka University/RIKEN AIP (Shizuoka Univ./RIKEN AIP)
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Speaker Author-1 
Date Time 2026-03-27 14:00:00 
Presentation Time 30 minutes 
Registration for BioX 
Paper # BioX2025-101, CNR2025-20 
Volume (vol) vol.125 
Number (no) no.426(BioX), no.427(CNR) 
Page pp.38-43 
#Pages 6 
Date of Issue 2026-03-19 (BioX, CNR) 

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