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cs.CV2026

When Surfaces Lie: Exploiting Wrinkle-Induced Attention Shift to Attack Vision-Language Models

Chengyin Hu, Xuemeng Sun, Jiaju Han +5

Visual-Language Models (VLMs) have demonstrated exceptional cross-modal understanding across various tasks, including zero-shot classification, image captioning, and visual questio…

cs.CV2026

A Semantic Decoupling-Based Two-Stage Rainy-Day Attack for Revealing Weather Robustness Deficiencies in Vision-Language Models

Chengyin Hu, Xiang Chen, Zhe Jia +4

Vision-Language Models (VLMs) are trained on image-text pairs collected under canonical visual conditions and achieve strong performance on multimodal tasks. However, their robustn…

cs.CV2025

VUGEN: Visual Understanding priors for GENeration

Xiangyi Chen, Théophane Vallaeys, Maha Elbayad +2

Recent advances in Vision-Language Models (VLMs) have enabled unified understanding across text and images, yet equipping these models with robust image generation capabilities rem…

cs.CV2025

DeLiVR: Differential Spatiotemporal Lie Bias for Efficient Video Deraining

Shuning Sun, Jialang Lu, Xiang Chen +5

Videos captured in the wild often suffer from rain streaks, blur, and noise. In addition, even slight changes in camera pose can amplify cross-frame mismatches and temporal artifac…

cs.CV2025

HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding

Jiaxing Zhao, Qize Yang, Yixing Peng +8

In human-centric scenes, the ability to simultaneously understand visual and auditory information is crucial. While recent omni models can process multiple modalities, they general…

cs.CV2025

Facial Dynamics in Video: Instruction Tuning for Improved Facial Expression Perception and Contextual Awareness

Jiaxing Zhao, Boyuan Sun, Xiang Chen +1

Facial expression captioning has found widespread application across various domains. Recently, the emergence of video Multimodal Large Language Models (MLLMs) has shown promise in…