1. Aghasanli, A., Kangin, D., Angelov, P., 2023. Interpretable-through-prototypes deepfake detection for diffusion models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision. pp. 467–474.
2. Deep learning for multimedia forensics;Amerini;Found. Trends Comput. Graph. Vis.,2021
3. Parents and children: Distinguishing multimodal deepfakes from natural images;Amoroso,2023
4. What makes fake images detectable? understanding properties that generalize;Chai,2020
5. Ciamarra, A., Caldelli, R., Becattini, F., Seidenari, L., Del Bimbo, A., 2024. Deepfake detection by exploiting surface anomalies: the SurFake approach. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. pp. 1024–1033.