Figure 2 - available via license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
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The first row visualizes victim images and victim objects highlighted with yellow bounding boxes. The second, third and forth row are the corresponding target labels generated with R1-5, R1-50 and R1-95, respectively.
Source publication
Adversarial attacks aims to perturb images such that a predictor outputs incorrect results. Due to the limited research in structured attacks, imposing consistency checks on natural multi-object scenes is a promising yet practical defense against conventional adversarial attacks. More desired attacks, to this end, should be able to fool defenses wi...
Context in source publication
Context 1
... we collect three target c p s according to v d (c p ). Specifically, we rank all c p / ∈ S d n based on v d (c p ) then followed by selecting the top 5%, 50% and 95% category as our requested target class. We refer these three attack requests as R1-95, R1-50 and R1-5, respectively. And we demonstrate our target label for each attack request in Fig. ...
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