On Physical Adversarial Patches for Object Detection

June 20, 2019 Β· Declared Dead Β· πŸ› arXiv.org

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Authors Mark Lee, Zico Kolter arXiv ID 1906.11897 Category cs.CV: Computer Vision Cross-listed cs.CR, cs.LG, stat.ML Citations 193 Venue arXiv.org Last Checked 4 months ago
Abstract
In this paper, we demonstrate a physical adversarial patch attack against object detectors, notably the YOLOv3 detector. Unlike previous work on physical object detection attacks, which required the patch to overlap with the objects being misclassified or avoiding detection, we show that a properly designed patch can suppress virtually all the detected objects in the image. That is, we can place the patch anywhere in the image, causing all existing objects in the image to be missed entirely by the detector, even those far away from the patch itself. This in turn opens up new lines of physical attacks against object detection systems, which require no modification of the objects in a scene. A demo of the system can be found at https://youtu.be/WXnQjbZ1e7Y.
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