Search Results for author:
Found 6 papers, 3 papers with code
Pruning for Robust Concept Erasing in Diffusion Models
Experimental results show a significant enhancement in our model's ability to resist adversarial inputs, achieving nearly a 40% improvement in erasing the NSFW content and a 30% improvement in erasing artwork style.
Model Synthesis for Zero-Shot Model Attribution
The design of the synthesis technique is motivated by observations on how the basic generative model's architecture building blocks and parameters influence fingerprint patterns, and it is validated through two designed metrics that examine synthetic models' fidelity and diversity.
Progressive Open Space Expansion for Open-Set Model Attribution
In this study, we focus on a challenging task, namely Open-Set Model Attribution (OSMA), to simultaneously attribute images to known models and identify those from unknown ones.
Deepfake Network Architecture Attribution
With the rapid progress of generation technology, it has become necessary to attribute the origin of fake images.
Learning to Disentangle GAN Fingerprint for Fake Image Attribution
Adopting a multi-task framework, we propose a GAN Fingerprint Disentangling Network (GFD-Net) to simultaneously disentangle the fingerprint from GAN-generated images and produce a content-irrelevant representation for fake image attribution.
Exploiting Multi-domain Visual Information for Fake News Detection
In the real world, fake-news images may have significantly different characteristics from real-news images at both physical and semantic levels, which can be clearly reflected in the frequency and pixel domain, respectively.
