3 accepted papers
Autonomous driving has made substantial progress recently, achieving reliable performance in most real-world environments. However, existing algorithms still depend heavily on high-definition maps, making them ineffective in mapless scenarios such as indoor parking lots. These limitations hinder sea
Recent advances in diffusion models have demonstrated impressive capability in generating high-quality images for simple prompts. However, when confronted with complex prompts involving multiple objects and hierarchical structures, existing models struggle to accurately follow instructions, leading
Monocular 3D object detection has become a mainstream approach in automatic driving for its easy application. A prominent advantage is that it does not need LiDAR point clouds during the inference. However, most current methods still rely on 3D point cloud data for labeling the ground truths used in…