6 papers
Diffusion-Guided Adversarial Perturbation Injection for Generalizable Defense Against Facial Manipulations
Yue Li, Linying Xue, Kaiqing Lin +5
Recent advances in GAN and diffusion models have significantly improved the realism and controllability of facial deepfake manipulation, raising serious concerns regarding privacy,…
TriniMark: A Robust Generative Speech Watermarking Method for Trinity-Level Traceability
Yue Li, Weizhi Liu, Kaiqing Lin +2
Diffusion-based speech generation has achieved remarkable fidelity, increasing the risk of misuse and unauthorized redistribution. However, most existing generative speech watermar…
An Efficient Watermarking Method for Latent Diffusion Models via Low-Rank Adaptation and Dynamic Loss Weighting
Dongdong Lin, Yue Li, Benedetta Tondi +3
The rapid proliferation of Deep Neural Networks (DNNs) is driving a surge in model watermarking technologies, as the trained models themselves constitute valuable intellectual prop…
Towards Imperceptible Adversarial Defense: A Gradient-Driven Shield against Facial Manipulations
Yue Li, Linying Xue, Dongdong Lin +3
With the flourishing prosperity of generative models, manipulated facial images have become increasingly accessible, raising concerns regarding privacy infringement and societal tr…
Protecting Your Voice: Temporal-aware Robust Watermarking
Yue Li, Weizhi Liu, Dongdong Lin +2
The rapid advancement of generative models has led to the synthesis of real-fake ambiguous voices. To erase the ambiguity, embedding watermarks into the frequency-domain features o…
SOLIDO: A Robust Watermarking Method for Speech Synthesis via Low-Rank Adaptation
Yue Li, Weizhi Liu, Dongdong Lin
The accelerated advancement of speech generative models has given rise to security issues, including model infringement and unauthorized abuse of content. Although existing generat…