Leveraging Vision-Language Models for Efficient Understanding of Vulnerable Roadway Users via a Multimodal Traffic Sensing Approach
The proliferation of 3D and video data from urban intersections offers a unique opportunity to analyze and protect vulnerable road users (VRUs). However, the effectiveness of modern detection models like PointPillar or CenterPoint is limited by the availability of high-quality labeled data. In Year 2, we demonstrated the feasibility of multimodal sensing using LiDAR and […]