Adversarial camera stickers: A physical camera-based attack on deep learning systems Adversarial camera stickers: A physical camera-based attack on deep learning systems
Paper summary Li et al. propose camera stickers that when computed adversarially and physically attached to the camera leads to mis-classification. As illustrated in Figure 1, these stickers are realized using circular patches of uniform color. These individual circular stickers are computed in a gradient-descent fashion by optimizing their location, color and radius. The influence of the camera on these stickers is modeled realistically in order to guarantee success. https://i.imgur.com/xHrqCNy.jpg Figure 1: Illustration of adversarial stickers on the camera (left) and the effect on the taken photo (right). Also find this summary at [davidstutz.de](https://davidstutz.de/category/reading/).
arxiv.org
scholar.google.com
Adversarial camera stickers: A physical camera-based attack on deep learning systems
Li, Juncheng and Schmidt, Frank R. and Kolter, J. Zico
arXiv e-Print archive - 2019 via Local Bibsonomy
Keywords: dblp


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Summary by David Stutz 2 weeks ago
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