Boosting the Transferability of Video Adversarial Examples via Temporal Translation
Boosting the Transferability of Video Adversarial Examples via Temporal Translation
Although deep-learning based video recognition models have achieved remarkable success, they are vulnerable to adversarial examples that are generated by adding human-imperceptible perturbations on clean video samples. As indicated in recent studies, adversarial examples are transferable, which makes it feasible for black-box attacks in real-world applications. Nevertheless, most existing adversarial …