Localizing manipulations in fully regenerated (FR) images

Establish image forgery localization techniques that can identify and delineate manipulated regions in fully regenerated images produced by text-guided inpainting, where the entire image is regenerated during editing and traditional forensic traces are weakened or destroyed.

Background

The paper distinguishes between spliced edits and fully regenerated (FR) edits in text-guided inpainting. In FR edits, the generative model may subtly alter the entire image while only semantically changing the masked region, which disrupts conventional forensic traces relied upon by image forgery localization (IFL) methods.

Prior work and the expanded TGIF2 benchmark show that current IFL methods perform well on spliced forgeries but largely fail to localize manipulations in FR images, while synthetic image detection (SID) methods are not designed for localization. The authors emphasize that robust localization in FR scenarios remains unresolved.