Catoptric Light can be Dangerous: Effective Physical-World Attack by Natural Phenomenon. (arXiv:2209.11739v1 [cs.CV])

Deep neural networks (DNNs) have achieved great success in many tasks.
Therefore, it is crucial to evaluate the robustness of advanced DNNs. The
traditional methods use stickers as physical perturbations to fool the
classifiers, which is difficult to achieve stealthiness and there exists
printing loss. Some new types of physical attacks use light beam to perform
attacks (e.g., laser, projector), whose optical patterns are artificial rather
than natural. In this work, we study a new type of physical attack, called …

attack physical world