2D-FACT: Dual-Domain Fake Image Detection Against Text-to-Image Generative Models | |
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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
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Date Published |
oct
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URL |
https://ieeexplore.ieee.org/document/10535000
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DOI |
10.1109/URTC60662.2023.10535000
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Google Scholar | BibTeX | DOI |