4 papers
Debiased Dual-Invariant Defense for Adversarially Robust Person Re-Identification
Yuhang Zhou, Yanxiang Zhao, Zhongyun Hua +4
Person re-identification (ReID) is a fundamental task in many real-world applications such as pedestrian trajectory tracking. However, advanced deep learning-based ReID models are…
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks
Lei Zhang, Yuhang Zhou, Yi Yang +1
Despite providing high-performance solutions for computer vision tasks, the deep neural network (DNN) model has been proved to be extremely vulnerable to adversarial attacks. Curre…
Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay
Yuhang Zhou, Zhongyun Hua
Deep neural networks have demonstrated susceptibility to adversarial attacks. Adversarial defense techniques often focus on one-shot setting to maintain robustness against attack.…
Invariance-powered Trustworthy Defense via Remove Then Restore
Xiaowei Fu, Yuhang Zhou, Lina Ma +1
Adversarial attacks pose a challenge to the deployment of deep neural networks (DNNs), while previous defense models overlook the generalization to various attacks. Inspired by tar…