2D-FACT: Dual-Domain Fake Image Detection Against Text-to-Image Generative Models
Author
Abstract

Recent developments in generative artificial intelligence are bringing great concerns for privacy, security and misinformation. Our work focuses on the detection of fake images generated by text-to-image models. We propose a dual-domain CNN-based classifier that utilizes image features in both the spatial and frequency domain. Through an extensive set of experiments, we demonstrate that the frequency domain features facilitate high accuracy, zero-transfer learning between different generative models, and faster convergence. To our best knowledge, this is the first effective detector against generative models that are finetuned for a specific subject.

Year of Publication
2023
Date Published
oct
URL
https://ieeexplore.ieee.org/document/10535000
DOI
10.1109/URTC60662.2023.10535000
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