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20232026
most citedCCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Model

1 citations · 2 across the 8 of their papers we have counts for

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cs.CV2026

BadAction: Backdoor Attacks on Interactive Video Generation via Action-Guided Triggers

Zhihang Wu, Zhongqi Wang, Jie Zhang +3

Interactive video generation (IVG) models have achieved remarkable progress in producing controllable visual content guided by user-defined actions, yet their security vulnerabilit…

cs.CV2026

EntropyScan: Towards Model-level Backdoor Detection in LVLMs via Visual Attention Entropy

Xuanyu Ge, Zhongqi Wang, Jie Zhang +2

Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across various tasks, yet they remain vulnerable to backdoor attacks. Existing defense methods predom…

cs.CV2026

What Makes VLMs Robust? Towards Reconciling Robustness and Accuracy in Vision-Language Models

Sen Nie, Jie Zhang, Zhongqi Wang +3

Achieving adversarial robustness in Vision-Language Models (VLMs) inevitably compromises accuracy on clean data, presenting a long-standing and challenging trade-off. In this work,…

cs.CV2025

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…

cs.CV2025

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.…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024★ 1 cited

T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models

Zhongqi Wang, Jie Zhang, Shiguang Shan +1

While text-to-image diffusion models demonstrate impressive generation capabilities, they also exhibit vulnerability to backdoor attacks, which involve the manipulation of model ou…

cs.CV2023★ 1 cited

CCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Model

Zhongqi Wang, Jie Zhang, Zhilong Ji +2

With the development of deep generative models, recent years have seen great success of Chinese landscape painting generation. However, few works focus on controllable Chinese land…