Adversarial Example Generation Method for Vehicle Environment Perception System

Abstract:

A method of generating adversarial examples against object detectors was proposed for object detection system in vehicle environment perception scenarios. The method achieves white-box adversarial attacks on object detectors， i.e.， object invisible attacks and object targeted mis-detectable attacks. On the Rail dataset and Cityscapes dataset， experimental results indicate that the method has good performance on the object invisible attacks and the object targeted mis-detectable attacks in the process of YOLO object detection.