57 citations · 125 across the 36 of their papers we have counts for
9 papers · 1 filter
Steering Vision-Language Pre-trained Models for Incremental Face Presentation Attack Detection
Haoze Li, Jie Zhang, Guoying Zhao +2
Face Presentation Attack Detection (PAD) demands incremental learning (IL) to combat evolving spoofing tactics and domains. Privacy regulations, however, forbid retaining past data…
Dual Attention Guided Defense Against Malicious Edits
Jie Zhang, Shuai Dong, Shiguang Shan +1
Recent progress in text-to-image diffusion models has transformed image editing via text prompts, yet this also introduces significant ethical challenges from potential misuse in c…
Semantic Mismatch and Perceptual Degradation: A New Perspective on Image Editing Immunity
Shuai Dong, Jie Zhang, Guoying Zhao +2
Text-guided image editing via diffusion models, while powerful, raises significant concerns about misuse, motivating efforts to immunize images against unauthorized edits using imp…
Towards Transferable Defense Against Malicious Image Edits
Jie Zhang, Shuai Dong, Shiguang Shan +1
Recent approaches employing imperceptible perturbations in input images have demonstrated promising potential to counter malicious manipulations in diffusion-based image editing sy…
Assimilation Matters: Model-level Backdoor Detection in Vision-Language Pretrained Models
Zhongqi Wang, Jie Zhang, Shiguang Shan +1
Vision-language pretrained models (VLPs) such as CLIP have achieved remarkable success, but are also highly vulnerable to backdoor attacks. Given a model fine-tuned by an untrusted…
V-Attack: Targeting Disentangled Value Features for Controllable Adversarial Attacks on LVLMs
Sen Nie, Jie Zhang, Jianxin Yan +2
Adversarial attacks have evolved from simply disrupting predictions on conventional task-specific models to the more complex goal of manipulating image semantics on Large Vision-La…
Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models
Zhongqi Wang, Jie Zhang, Shiguang Shan +1
Recent studies have revealed that text-to-image diffusion models are vulnerable to backdoor attacks, where attackers implant stealthy textual triggers to manipulate model outputs.…
REVAL: A Comprehension Evaluation on Reliability and Values of Large Vision-Language Models
Jie Zhang, Zheng Yuan, Zhongqi Wang +6
The rapid evolution of Large Vision-Language Models (LVLMs) has highlighted the necessity for comprehensive evaluation frameworks that assess these models across diverse dimensions…
Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models
Jie Zhang, Zhongqi Wang, Shiguang Shan +1
Backdoor attacks targeting text-to-image diffusion models have advanced rapidly. However, current backdoor samples often exhibit two key abnormalities compared to benign samples: 1…