Whodunit: Detection and Attribution of Synthetic Images by Leveraging Model-specific Fingerprints
Alexander Wißmann, Steffen Zeiler, Robert M. Nickel, Dorothea Kolossa · 2024
With increasingly easier access to large, pre-trained text-to-image models, a surge of synthetic images, often visually indistinguishable from natural images, can be observed. Since naturalistic, synthetic images can be misidentified as natural, a general mistrust in visually conveyed information could be the result, especially considering misinformation potentially carried by synthetic images. The reverse case—misidentifying natural images as synthetic—may also contribute to this outcome. Detection and attribution of synthetic images can provide essential information about the source of an image, thus contributing to a realistic evaluation of its credibility.