8 citations · 8 across the 6 of their papers we have counts for
6 papers · 1 filter
Dynamic Semantic-Aware Correlation Modeling for UAV Tracking
Xinyu Zhou, Tongxin Pan, Lingyi Hong +5
UAV tracking can be widely applied in scenarios such as disaster rescue, environmental monitoring, and logistics transportation. However, existing UAV tracking methods predominantl…
Enhancing Diffusion-based Unrestricted Adversarial Attacks via Adversary Preferences Alignment
Kaixun Jiang, Zhaoyu Chen, Haijing Guo +6
Preference alignment in diffusion models has primarily focused on benign human preferences (e.g., aesthetic). In this paper, we propose a novel perspective: framing unrestricted ad…
Boosting Adversarial Transferability with Spatial Adversarial Alignment
Zhaoyu Chen, Haijing Guo, Kaixun Jiang +6
Deep neural networks are vulnerable to adversarial examples that exhibit transferability across various models. Numerous approaches are proposed to enhance the transferability of a…
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…
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…
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…