Radar Perception

Radar perception focuses on extracting meaningful information from radar signals to enable applications like autonomous driving and indoor navigation. Current research emphasizes improving the accuracy and density of radar data representations, often using deep learning techniques such as multi-task learning and diffusion models to enhance point cloud generation and fusion with other sensor modalities (e.g., cameras). These advancements are crucial for robust object detection, pose estimation, and scene understanding in challenging environments, ultimately improving the safety and reliability of autonomous systems and other applications requiring precise environmental awareness.