Reflective Adversarial Attacks against Pedestrian Detection Systems for Vehicles at Night
Yuanwan Chen,
Yalun Wu,
Xiaoshu Cui
et al.
Abstract:The advancements in deep learning have significantly enhanced the accuracy and robustness of pedestrian detection. However, recent studies reveal that adversarial attacks can exploit the vulnerabilities of deep learning models to mislead detection systems. These attacks are effective not only in digital environments but also pose significant threats to the reliability of pedestrian detection systems in the physical world. Existing adversarial attacks targeting pedestrian detection primarily focus on daytime sc… Show more
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