Adversarial Semantic Contour for Object Detection

Understand

Modern object detectors are vulnerable to adversarial examples, which brings potential risks to numerous applications, e.g., self-driving car.

• Among attacks regularized by $\ell_p$ norm, $\ell_0$-attack aims to modify as few pixels as possible.
• Nevertheless, the problem is nontrivial since it generally requires to optimize the shape along with the texture simultaneously, which is an NP-hard problem.
• To address this issue, we propose a novel method of Adversarial Semantic Contour (ASC) guided by object contour as prior.