A siamese-based verification system for open-set architecture attribution of synthetic images

Lydia Abady, Jun Wang, Benedetta Tondi, Mauro Barni

Abstract: Highlights•New verification framework for open-set architecture attribution of synthetic images.•Tested with several types of generative architectures in closed and open set scenarios.•Generalization tests prove that the system can verify unknown models of the architecture.•Outperforms state-of-the-art methods for open-set architecture attribution with rejection.