Sep, 2023
抵御对抗性补丁攻击的 RGB-D 物体识别系统强化
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks
Yang Zheng, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia...
TL;DRRGB-D object recognition systems are vulnerable to adversarial examples, and color features contribute to this weakness, making the network more sensitive to perturbations. To address this issue, a defense mechanism is proposed, which improves the performance of RGB-D systems against adversarial examples and exceeds the effectiveness of adversarial training.