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MSAFNet: Multi-Scale Self-Adaptive Feature Fusion Network for AI-Generated Image Detection

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Proposed MSAFNet enhances detection accuracy of ai-generated images by integrating feature fusion techniques.

MSAFNet improves detection accuracy for ai-generated images through enhanced feature fusion techniques.
The method captures global noise patterns and subtle texture anomalies, outperforming traditional approaches.
Experimental validation on DFFD and CIFAKE datasets shows significant performance improvements over existing detection methods.
This approach addresses the detection challenges posed by both known and emerging generative technologies.

Yao et al. (2025) studied this question.

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