Pedestrian Detection

Pedestrian detection, a crucial task in computer vision, aims to accurately and efficiently identify pedestrians in images and videos, primarily for applications like autonomous driving and surveillance. Current research emphasizes improving robustness in challenging conditions (low light, occlusion, adverse weather) through the use of lightweight deep learning models (like optimized YOLO variants), multi-modal fusion (combining RGB, thermal, LiDAR, and event camera data), and advanced post-processing techniques. These advancements are vital for enhancing the safety and reliability of autonomous systems and improving the performance of various computer vision applications.