Intersection Scenario

Intersection scenarios, encompassing diverse applications from traffic management to object detection and 3D vision, focus on improving efficiency and safety where multiple entities converge. Current research utilizes various approaches, including reinforcement learning for traffic control, deep learning models (like UNet and DETR variants) for image processing and object tracking, and novel loss functions (e.g., Gr-IoU, Focaler-IoU) to enhance accuracy. These advancements are significant for improving autonomous systems, optimizing urban infrastructure, and enhancing the reliability of machine learning models in complex environments.