5 papers
Mixture-of-Modality-Experts with Holistic Token Learning for Fine-Grained Multimodal Visual Analytics in Driver Action Recognition
Tianyi Liu, Yiming Li, Wenqian Wang +4
Robust multimodal visual analytics remains challenging when heterogeneous modalities provide complementary but input-dependent evidence for decision-making.Existing multimodal lear…
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…
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…
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…
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…