Adversarial Rain Attack and Defensive Deraining for DNN Perception. (arXiv:2009.09205v2 [cs.CV] UPDATED)

Rain often poses inevitable threats to deep neural network (DNN) based
perception systems, and a comprehensive investigation of the potential risks of
the rain to DNNs is of great importance. However, it is rather difficult to
collect or synthesize rainy images that can represent all rain situations that
would possibly occur in the real world. To this end, in this paper, we start
from a new perspective and propose to combine two totally different studies,
i.e., rainy image synthesis and …

attack defensive