Pedestrian Detector

Pedestrian detection, a crucial component of autonomous driving and surveillance systems, aims to accurately identify and locate pedestrians in images or video. Current research focuses on improving detection accuracy, particularly in challenging conditions like occlusion, nighttime, and diverse demographics, often employing deep learning models such as convolutional neural networks (CNNs) and exploring techniques like post-processing and data augmentation to mitigate biases and improve robustness. Addressing fairness concerns, such as biases related to age and gender, and developing more generalizable models that perform well across different datasets are also significant areas of investigation, with implications for the safety and reliability of autonomous systems.