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cs.CV2026

DAOS: A Multimodal In-cabin Behavior Monitoring with Driver Action-Object Synergy Dataset

Yiming Li, Chen Cai, Tianyi Liu +5

In driver activity monitoring, movements are mostly limited to the upper body, which makes many actions look similar. To tell these actions apart, human often rely on the objects t…

cs.CV2024

Open World Object Detection: A Survey

Yiming Li, Yi Wang, Wenqian Wang +3

Exploring new knowledge is a fundamental human ability that can be mirrored in the development of deep neural networks, especially in the field of object detection. Open world obje…

cs.CV2024

MultiFuser: Multimodal Fusion Transformer for Enhanced Driver Action Recognition

Ruoyu Wang, Wenqian Wang, Jianjun Gao +3

Driver action recognition, aiming to accurately identify drivers' behaviours, is crucial for enhancing driver-vehicle interactions and ensuring driving safety. Unlike general actio…

cs.CV2024

CM2-Net: Continual Cross-Modal Mapping Network for Driver Action Recognition

Ruoyu Wang, Chen Cai, Wenqian Wang +4

Driver action recognition has significantly advanced in enhancing driver-vehicle interactions and ensuring driving safety by integrating multiple modalities, such as infrared and d…

cs.CV2024

Multi-modality action recognition based on dual feature shift in vehicle cabin monitoring

Dan Lin, Philip Hann Yung Lee, Yiming Li +4

Driver Action Recognition (DAR) is crucial in vehicle cabin monitoring systems. In real-world applications, it is common for vehicle cabins to be equipped with cameras featuring di…