Pedestrian Recognition

Pedestrian recognition, a crucial aspect of computer vision, aims to accurately identify and track individuals in various settings, driving advancements in autonomous vehicles and surveillance systems. Current research emphasizes improving robustness against challenges like occlusion, pose variations, and changing clothing, often employing deep learning architectures such as convolutional neural networks (CNNs), transformers, and generative models, sometimes incorporating data from multiple sensor modalities (e.g., radar and LiDAR). These improvements are vital for enhancing the reliability and safety of applications ranging from traffic monitoring to security systems.