3 citations · 12 across the 33 of their papers we have counts for
15 papers · 1 filter
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…
T2VAttack: Adversarial Attack on Text-to-Video Diffusion Models
Changzhen Li, Yuecong Min, Jie Zhang +3
The rapid evolution of Text-to-Video (T2V) diffusion models has driven remarkable advancements in generating high-quality, temporally coherent videos from natural language descript…
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…
VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task
Xingming Long, Jie Zhang, Shiguang Shan +1
Most research on hallucinations in Large Vision-Language Models (LVLMs) focuses on factual description tasks that prohibit any output absent from the image. However, little attenti…
GLip: A Global-Local Integrated Progressive Framework for Robust Visual Speech Recognition
Tianyue Wang, Shuang Yang, Shiguang Shan +1
Visual speech recognition (VSR), also known as lip reading, is the task of recognizing speech from silent video. Despite significant advancements in VSR over recent decades, most e…
Jodi: Unification of Visual Generation and Understanding via Joint Modeling
Yifeng Xu, Zhenliang He, Meina Kan +2
Visual generation and understanding are two deeply interconnected aspects of human intelligence, yet they have been traditionally treated as separate tasks in machine learning. In…
Plan-R1: Safe and Feasible Trajectory Planning as Language Modeling
Xiaolong Tang, Meina Kan, Shiguang Shan +1
Safe and feasible trajectory planning is critical for real-world autonomous driving systems. However, existing learning-based planners rely heavily on expert demonstrations, which…
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.…
EfficientMT: Efficient Temporal Adaptation for Motion Transfer in Text-to-Video Diffusion Models
Yufei Cai, Hu Han, Yuxiang Wei +2
The progress on generative models has led to significant advances on text-to-video (T2V) generation, yet the motion controllability of generated videos remains limited. Existing mo…
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…
MATS: An Audio Language Model under Text-only Supervision
Wen Wang, Ruibing Hou, Hong Chang +2
Large audio-language models (LALMs), built upon powerful Large Language Models (LLMs), have exhibited remarkable audio comprehension and reasoning capabilities. However, the traini…