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Paper Abstract and Keywords
Presentation 2025-09-18 14:20
CAGE: Controllable Agent Generation in Driving Scenes via Vision-Language Models
Yibin Chen (UTokyo), Yanlei Gu (Hiroshima Univ.), Shunsuke Kamijo (UTokyo) ITS2025-6
Abstract (in Japanese) (See Japanese page) 
(in English) The safety and reliability of autonomous driving systems depend on their robustness in complex scenarios underrepresented in training data. However, prevailing data augmentation techniques are predominantly limited to the Bird's-Eye View (BEV), failing to incorporate critical camera-perspective cues such as traffic lights and roadside signs, thus compromising the model's ability to handle context-rich scenarios. To address this limitation, we introduce textbf{CAGE} (Controllable Agent GEneration), a framework for generating traffic agents based on human instructions. At its core, CAGE achieves semantic and geometric consistency through a two-stage process. First, a Vision-Language Model (VLM) interprets the user's instruction and visual context in camera views to generate a high-level proposal, specifying the agent's attributes and coarse trajectory. This proposal is then refined by a spatiotemporal Transformer, which leverages precise geometric data from the BEV to produce a kinematically feasible trajectory. Extensive evaluations on the nuScenes dataset demonstrate the method's effectiveness in generating high-quality, contextually appropriate traffic agents.
Keyword (in Japanese) (See Japanese page) 
(in English) Autonomous Driving / Data Augmentation / Traffic Agent Generation / Controllable Generation / Vision-Language Model / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 183, ITS2025-6, pp. 1-6, Sept. 2025.
Paper # ITS2025-6 
Date of Issue 2025-09-11 (ITS) 
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 ITS2025-6

Conference Information
Committee ITS IPSJ-ITS IEE-ITS  
Conference Date 2025-09-18 - 2025-09-19 
Place (in Japanese) (See Japanese page) 
Place (in English) CRANTS Gunma Univ. (in Aramaki) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ITS 
Conference Code 2025-09-ITS-ITS-ITS 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) CAGE: Controllable Agent Generation in Driving Scenes via Vision-Language Models 
Sub Title (in English)  
Keyword(1) Autonomous Driving  
Keyword(2) Data Augmentation  
Keyword(3) Traffic Agent Generation  
Keyword(4) Controllable Generation  
Keyword(5) Vision-Language Model  
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1st Author's Name Yibin Chen  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Yanlei Gu  
2nd Author's Affiliation Hiroshima University (Hiroshima Univ.)
3rd Author's Name Shunsuke Kamijo  
3rd Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2025-09-18 14:20:00 
Presentation Time 25 minutes 
Registration for ITS 
Paper # ITS2025-6 
Volume (vol) vol.125 
Number (no) no.183 
Page pp.1-6 
#Pages 6 
Date of Issue 2025-09-11 (ITS) 

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