Hardening RGB-D object recognition systems against adversarial patch attacks

Yang Zheng, Luca Demetrio, Antonio Emanuele Cinà, Xiaoyi Feng, Zhaoqiang Xia, Xiaoyue Jiang, Ambra Demontis, Battista Biggio, Fabio Roli

Abstract: Highlights•We assess the performance of a state-of-art system for object detection based on color and depth features.•We explain why RGB features are more vulnerable to attacks than depth features.•We develop a defense against adversarial examples.