7 papers
LINA: Linear Autoregressive Image Generative Models with Continuous Tokens
Jiahao Wang, Ting Pan, Haoge Deng +4
Autoregressive models with continuous tokens form a promising paradigm for visual generation, especially for text-to-image (T2I) synthesis, but they suffer from high computational…
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
Despite recent advancements in federated learning (FL), the integration of generative models into FL has been limited due to challenges such as high communication costs and unstabl…
KAN See Your Face
Dong Han, Yong Li, Joachim Denzler
With the advancement of face reconstruction (FR) systems, privacy-preserving face recognition (PPFR) has gained popularity for its secure face recognition, enhanced facial privacy…
ShieldDiff: Suppressing Sexual Content Generation from Diffusion Models through Reinforcement Learning
Dong Han, Salaheldin Mohamed, Yong Li
With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, the generated contents cannot be fully controlled. There is…
Fusion is all you need: Face Fusion for Customized Identity-Preserving Image Synthesis
Salaheldin Mohamed, Dong Han, Yong Li
Text-to-image (T2I) models have significantly advanced the development of artificial intelligence, enabling the generation of high-quality images in diverse contexts based on speci…
Robust Skin Color Driven Privacy Preserving Face Recognition via Function Secret Sharing
Dong Han, Yufan Jiang, Yong Li +2
In this work, we leverage the pure skin color patch from the face image as the additional information to train an auxiliary skin color feature extractor and face recognition model…
Privacy-Preserving Face Recognition in Hybrid Frequency-Color Domain
Dong Han, Yong Li, Joachim Denzler
Face recognition technology has been deployed in various real-life applications. The most sophisticated deep learning-based face recognition systems rely on training millions of fa…