STA: Adversarial Attacks on Siamese Trackers

Understand

Recently, the majority of visual trackers adopt Convolutional Neural Network (CNN) as their backbone to achieve high tracking accuracy.

• However, less attention has been paid to the potential adversarial threats brought by CNN, including Siamese network.
• In this paper, we first analyze the existing vulnerabilities in Siamese trackers and propose the requirements for a successful adversarial attack.
• On this basis, we formulate the adversarial generation problem and propose an end-to-end pipeline to generate a perturbed texture map for the 3D object that causes the trackers to fail.