Yicheng Qiao — accepted AI-conference papers

2025

MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception

Wenzhuo Liu, Wenshuo Wang, Yicheng Qiao, Qiannan Guo, Jiayin Zhu, Pengfei Li +6

CVPR 2025poster

Advanced driver assistance systems require a comprehensive understanding of the driver's mental/physical state and traffic context but existing works often neglect the potential benefits of joint learning between these tasks. This paper proposes MMTL-UniAD, a unified multi-modal multi-task learning…

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2025

TEM3-Learning: Time-Efficient Multimodal Multi-Task Learning for Advanced Assistive Driving

Wenzhuo Liu, Yicheng Qiao, Zhen Wang, Qiannan Guo, Zilong Chen, Meihua Zhou +5

IROS 2025

Multi-task learning (MTL) can advance assistive driving by exploring inter-task correlations through shared representations. However, existing methods face two critical limitations: single-modality constraints limiting comprehensive scene understanding and inefficient architectures impeding real-tim

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