most citedOpen World Object Detection: A Survey

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

collaborators

5 papers

cs.CV2026

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…

cs.CV2026

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,…

cs.CV2024★ 28 cited

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…