28 citations · 28 across the 5 of their papers we have counts for
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 +6
Multimodal action understanding requires complementary sensory observations to be connected with structured semantic knowledge. This is particularly challenging in vehicle cabins,…
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…