Abstract: In the realm of multimodal multi-object tracking (MOT) applications based on point clouds and images, the current research predominantly focuses on enhancing tracking accuracy, often ...

Stanford researchers have developed an innovative computer vision model that recognizes the real-world functions of objects, potentially allowing autonomous robots to select and use tools more ...

Abstract: The object point clouds acquired by the original LiDAR are inherently sparse and incomplete, resulting in suboptimal single object tracking (SOT) precision for 3D bounding boxes, especially ...