DPatch: An Adversarial Patch Attack on Object Detectors

Understand

Object detectors have emerged as an indispensable module in modern computer vision systems.

• In this work, we propose DPatch -- a black-box adversarial-patch-based attack towards mainstream object detectors (i.e.
• Faster R-CNN and YOLO).
• Unlike the original adversarial patch that only manipulates image-level classifier, our DPatch simultaneously attacks the bounding box regression and object classification so as to disable their predictions.