Yanqiu Xiao

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About

Yanqiu Xiao is a prominent researcher in computer vision, with a core focus on pedestrian detection and deep learning. Her most-cited work, a comprehensive 2020 review on deep learning for occluded and multi-scale pedestrian detection, has garnered 46 citations, establishing her as a key voice in this critical area. This paper systematically surveys the challenges and breakthroughs in detecting pedestrians under real-world conditions—such as partial occlusion and varying scales—which are essential for advancing autonomous driving, video surveillance, and robotics. By synthesizing the rapid evolution of deep learning techniques in this domain, Xiao’s review serves as a foundational resource for researchers tackling these persistent computer vision problems. Her contributions not only highlight the unprecedented progress in the field but also identify remaining hurdles, guiding future innovation. Through this influential work, Yanqiu Xiao has demonstrated a clear ability to distill complex technical landscapes, making her a valuable reference for students and engineers seeking to understand and improve pedestrian detection systems in dynamic, cluttered environments.