3 citations · 3 across the 1 of their papers we have counts for
3 papers
cs.CV2026★ 3 cited
MAPE: Defending Against Transferable Adversarial Attacks Using Multi-Source Adversarial Perturbations Elimination
Xinlei Liu, Jichao Xie, Tao Hu +4
Neural networks are vulnerable to meticulously crafted adversarial examples, leading to high-confidence misclassifications in image classification tasks. Due to their consistency w…
cs.CV2026
SDM: A Powerful Tool for Evaluating Model Robustness
Xinlei Liu, Tao Hu, Jichao Xie +3
Gradient-based attacks are important methods for evaluating model robustness. However, since the proposal of APGD, it has been difficult for such methods to achieve significant bre…
cs.CV2025
Sequential Difference Maximization: Generating Adversarial Examples via Multi-Stage Optimization
Xinlei Liu, Tao Hu, Peng Yi +3
Efficient adversarial attack methods are critical for assessing the robustness of computer vision models. In this paper, we reconstruct the optimization objective for generating ad…