5 papers
From Semantics, Scene to Instance-awareness: Distilling Foundation Model for Grounded Open-vocabulary Situation Recognition
Chen Cai, Tianyi Liu, Jianjun Gao +5
Recent Multimodal Large Language Models (MLLMs) exhibit strong zero-shot abilities but struggle with complex Grounded Situation Recognition (GSR) and are resource-intensive for edg…
CL-HOI: Cross-Level Human-Object Interaction Distillation from Vision Large Language Models
Jianjun Gao, Chen Cai, Ruoyu Wang +4
Human-object interaction (HOI) detection has seen advancements with Vision Language Models (VLMs), but these methods often depend on extensive manual annotations. Vision Large Lang…
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…