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cs.CV2025
Improving Adversarial Transferability with Neighbourhood Gradient Information
Haijing Guo, Jiafeng Wang, Zhaoyu Chen +5
Deep neural networks (DNNs) are known to be susceptible to adversarial examples, leading to significant performance degradation. In black-box attack scenarios, a considerable attac…
cs.CV2024
Boosting the Transferability of Adversarial Attacks with Global Momentum Initialization
Jiafeng Wang, Zhaoyu Chen, Kaixun Jiang +5
Deep Neural Networks (DNNs) are vulnerable to adversarial examples, which are crafted by adding human-imperceptible perturbations to the benign inputs. Simultaneously, adversarial…
cs.CV2024
Improving Adversarial Transferability of Vision-Language Pre-training Models through Collaborative Multimodal Interaction
Jiyuan Fu, Zhaoyu Chen, Kaixun Jiang +4
Despite the substantial advancements in Vision-Language Pre-training (VLP) models, their susceptibility to adversarial attacks poses a significant challenge. Existing work rarely s…