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Physical adversarial attacks against object detectors have seen increasingsuccess in recent years. However, these attacks require direct access to theobject of interest in order to apply a physical patch. Furthermore, to hidemultiple objects, an adversarial patch must be applied to each object. In thispaper, we propose a contactless translucent physical patch containing acarefully constructed pattern, which is placed on the camera's lens, to foolstate-of-the-art object detectors. The primary goal of our patch is to hide allinstances of a selected target class. In addition, the optimization method usedto construct the patch aims to ensure that the detection of other (untargeted)classes remains unharmed. Therefore, in our experiments, which are conducted onstate-of-the-art object detection models used in autonomous driving, we studythe effect of the patch on the detection of both the selected target class andthe other classes. We show that our patch was able to prevent the detection of42.27% of all stop sign instances while maintaining high (nearly 80%) detectionof the other classes.

The Translucent Patch: A Physical and Universal Attack on Object Detectors