Survey on adversarial attacks and defenses for object detection - Xinxin WANG; Jing CHEN; Kun HE; Zijun ZHANG; Ruiying DU; Qiao LI; Jisi SHE (Tongxin xuebao)
In response to recent developments in adversarial attacks and defenses for object detection, relevant terms and concepts associated with object detection and adversarial learning were first introduced.Subsequently, according to the evolution process of the methods, a comprehensive retrospective analysis was conducted on the research achievements in the realm of adversarial attacks and defense methods for object detection.Particularly, attack methods and defense strategies were categorized based on the attacker knowledge and the deep learning lifecycle.Furthermore, an in-depth analysis and discussion of the characteristics and relationships among different approaches were provided.Lastly, considering the strengths and limitations of existing research, the imminent challenges and directions were summarized for further exploration in adversarial attack and defense of object detection.