“Ugly shirt” that makes human silhouettes invisible to neural network AIs

Adafruit 2019 3539

[1910.11099] Adversarial T-shirt! Evading Person Detectors in A Physical World.

It is known that deep neural networks (DNNs) are vulnerable to adversarial attacks. The so-called physical adversarial examples deceive DNN-based decision makers by attaching adversarial patches to real objects. However, most of the existing works on physical adversarial attacks focus on static objects such as glass frames, stop signs and images attached to cardboard. In this work, we propose Adversarial T-shirts, a robust physical adversarial example for evading person detectors even if it could undergo non-rigid deformation due to a moving person’s pose changes. To the best of our knowledge, this is the first work that models the effect of deformation for designing physical adversarial examples with respect to non-rigid objects such as T-shirts. We show that the proposed method achieves 74% and 57% attack success rates in digital and physical worlds respectively against YOLOv2. In contrast, the state-of-the-art physical attack method to fool a person detector only achieves 18% attack success rate. Furthermore, by leveraging min-max optimization, we extend our method to the ensemble attack setting against two object detectors YOLO-v2 and Faster R-CNN simultaneously.

Read more, PDF, video .. .via Bruce Sterling and William Gibson. Also check out the short story “BLIT” and “Fantasy & Science Fiction v031n06 (1966 12) Von Goom’s Gambit by Victor Contoski.”


Ugly

Shirt appearing on https://mooteef.com/ in 3,2,1…


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