2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?
Ouxiang Li, Yuan Wang, Xinting Hu +7
Text-to-image (T2I) generation aims to synthesize images from textual prompts, which jointly specify what must be shown and imply what can be inferred, which thus correspond to two…
SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models
Ouxiang Li, Yuan Wang, Xinting Hu +3
Erasing concepts from large-scale text-to-image (T2I) diffusion models has become increasingly crucial due to the growing concerns over copyright infringement, offensive content, a…
Improving Synthetic Image Detection Towards Generalization: An Image Transformation Perspective
Ouxiang Li, Jiayin Cai, Yanbin Hao +3
With recent generative models facilitating photo-realistic image synthesis, the proliferation of synthetic images has also engendered certain negative impacts on social platforms,…
Model Inversion Attacks Through Target-Specific Conditional Diffusion Models
Ouxiang Li, Yanbin Hao, Zhicai Wang +4
Model inversion attacks (MIAs) aim to reconstruct private images from a target classifier's training set, thereby raising privacy concerns in AI applications. Previous GAN-based MI…