  Physical adversarial attacks against object detectors have seen increasing
success in recent years. However, these attacks require direct access to the
object of interest in order to apply a physical patch. Furthermore, to hide
multiple objects, an adversarial patch must be applied to each object. In this
paper, we propose a contactless translucent physical patch containing a
carefully constructed pattern, which is placed on the camera's lens, to fool
state-of-the-art object detectors. The primary goal of our patch is to hide all
instances of a selected target class. In addition, the optimization method used
to construct the patch aims to ensure that the detection of other (untargeted)
classes remains unharmed. Therefore, in our experiments, which are conducted on
state-of-the-art object detection models used in autonomous driving, we study
the effect of the patch on the detection of both the selected target class and
the other classes. We show that our patch was able to prevent the detection of
42.27% of all stop sign instances while maintaining high (nearly 80%) detection
of the other classes.
