28 citations · 28 across the 5 of their papers we have counts for
5 papers
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…
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…