Radar Based Perception

Radar-based perception aims to leverage radar sensors for robust and reliable scene understanding in applications like autonomous driving, particularly in challenging weather conditions. Current research focuses on improving the accuracy and efficiency of radar object detection and semantic segmentation using advanced deep learning architectures, such as graph neural networks and transformers, often incorporating data fusion with cameras to overcome the inherent sparsity and noise of radar data. These advancements are crucial for enhancing the safety and reliability of autonomous systems and improving the performance of advanced driver-assistance systems (ADAS).