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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…
PosterCopilot: Toward Layout Reasoning and Controllable Editing for Professional Graphic Design
Jiazhe Wei, Ken Li, Tianyu Lao +4
Graphic design forms the cornerstone of modern visual communication, serving as a vital medium for promoting cultural and commercial events. Recent advances have explored automatin…
GOOD: Training-Free Guided Diffusion Sampling for Out-of-Distribution Detection
Xin Gao, Jiyao Liu, Guanghao Li +8
Recent advancements have explored text-to-image diffusion models for synthesizing out-of-distribution (OOD) samples, substantially enhancing the performance of OOD detection. Howev…
Towards Real-Time Fake News Detection under Evidence Scarcity
Guangyu Wei, Ke Han, Yueming Lyu +4
Fake news detection becomes particularly challenging in real-time scenarios, where emerging events often lack sufficient supporting evidence. Existing approaches often rely heavily…
SpineBench: A Clinically Salient, Level-Aware Benchmark Powered by the SpineMed-450k Corpus
Ming Zhao, Wenhui Dong, Yang Zhang +23
Spine disorders affect 619 million people globally and are a leading cause of disability, yet AI-assisted diagnosis remains limited by the lack of level-aware, multimodal datasets.…
An Effective End-to-End Solution for Multimodal Action Recognition
Songping Wang, Xiantao Hu, Yueming Lyu +1
Recently, multimodal tasks have strongly advanced the field of action recognition with their rich multimodal information. However, due to the scarcity of tri-modal data, research o…
Ivy-Fake: A Unified Explainable Framework and Benchmark for Image and Video AIGC Detection
Changjiang Jiang, Wenhui Dong, Zhonghao Zhang +8
The rapid development of Artificial Intelligence Generated Content (AIGC) techniques has enabled the creation of high-quality synthetic content, but it also raises significant secu…
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos
Songping Wang, Hanqing Liu, Yueming Lyu +5
Adversarial Training (AT) has been shown to significantly enhance adversarial robustness via a min-max optimization approach. However, its effectiveness in video recognition tasks…
Anti-Aesthetics: Protecting Facial Privacy against Customized Text-to-Image Synthesis
Songping Wang, Yueming Lyu, Shiqi Liu +4
The rise of customized diffusion models has spurred a boom in personalized visual content creation, but also poses risks of malicious misuse, severely threatening personal privacy…
Exploring Adversarial Transferability between Kolmogorov-arnold Networks
Songping Wang, Xinquan Yue, Yueming Lyu +1
Kolmogorov-Arnold Networks (KANs) have emerged as a transformative model paradigm, significantly impacting various fields. However, their adversarial robustness remains less undere…