ManiFPT: Defining and Analyzing Fingerprints of Generative Models

arXiv:2402.10401v1 Announce Type: new
Abstract: Recent works have shown that generative models leave traces of their underlying generative process on the generated samples, broadly referred to as fingerprints of a generative model, and have studied their utility in detecting synthetic images from real ones. However, the extend to which these fingerprints can distinguish between various types of synthetic image and help identify the underlying generative process remain under-explored. In particular, the very definition of a fingerprint remains unclear, to our …

abstract arxiv cs.cv cs.lg fingerprints generated generative generative models images process samples synthetic traces type utility