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cs.CV2026

PRMU: A Corpus-Free Benchmark for Person-Centric Knowledge Unlearning in Multimodal Large Language Models

Huafeng Chen, Yueming Lyu, Ziyuan Chen +4

Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in storing and recalling rich person-related knowledge, raising increasing concerns about reliabl…

cs.CV2026

Is There Really a Camouflaged Object? Towards Realistic Camouflaged Object Detection

Huafeng Chen, Yueming Lyu, Chenyang Si +3

Camouflaged object detection (COD) aims to segment objects that are visually concealed in their surroundings and has attracted increasing attention in recent years. However, most e…

cs.CV2026

Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models

Songping Wang, Yueming Lyu, Shiqi Liu +5

The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious misuse, thereby posing threats…

cs.CV2026

Exposing and Defending the Achilles' Heel of Video Mixture-of-Experts

Songping Wang, Qinglong Liu, Yueming Lyu +3

Mixture-of-Experts (MoE) has demonstrated strong performance in video understanding tasks, yet its adversarial robustness remains underexplored. Existing attack methods often treat…

cs.CV2026

DiffusionAgent: Navigating Expert Models for Agentic Image Generation

Jie Qin, Jie Wu, Weifeng Chen +1

In the accelerating era of human-instructed visual content creation, diffusion models have demonstrated remarkable generative potential. Yet their deployment is constrained by a du…

cs.CV2025

RunawayEvil: Jailbreaking the Image-to-Video Generative Models

Songping Wang, Rufan Qian, Yueming Lyu +5

Image-to-Video (I2V) generation synthesizes dynamic visual content from image and text inputs, providing significant creative control. However, the security of such multimodal syst…