Regeneration Based Training-free Attribution of Fake Images Generated by Text-to-Image Generative Models

arXiv:2403.01489v1 Announce Type: new
Abstract: Text-to-image generative models have recently garnered significant attention due to their ability to generate images based on prompt descriptions. While these models have shown promising performance, concerns have been raised regarding the potential misuse of the generated fake images. In response to this, we have presented a simple yet effective training-free method to attribute fake images generated by text-to-image models to their source models. Given a test image to be attributed, we first inverse the …

abstract arxiv attention attribution concerns cs.ai cs.cv fake free generate generated generative generative models image images misuse performance prompt text text-to-image training type