Person Detector

Person detection, a core task in computer vision, aims to accurately identify and locate individuals within images or videos. Current research focuses on improving robustness against adversarial attacks (e.g., using specially designed clothing or patches to evade detection), enhancing accuracy by reducing false positives, and adapting to diverse sensor modalities (like 2D range finders) and challenging viewpoints (such as top-down omnidirectional views). These advancements leverage various deep learning architectures, including single-shot and two-stage detectors, often incorporating techniques like attention mechanisms and keypoint estimation to improve performance and efficiency. The resulting improvements have significant implications for applications such as autonomous driving, security systems, and robotics.