A Forensic Framework With Diverse Data Generation for Generalizable Forgery Localization
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DOI: 10.1109/tifs.2025.3607251
Abstract: Deep learning-based forensic techniques have emerged as the leading approach for image forgery localization. However, many existing methods struggle with overfitting to the training data, which limits their generalization performance and real-world applicability. To overcome… read more here.
Keywords: forensic framework; framework; forgery localization; data generation ... See more keywords