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Towards Robust GAN-generated Image Detection: a Multi-view Completion Representation. (arXiv:2306.01364v1 [cs.CR])
cs.CR updates on arXiv.org arxiv.org
GAN-generated image detection now becomes the first line of defense against
the malicious uses of machine-synthesized image manipulations such as
deepfakes. Although some existing detectors work well in detecting clean, known
GAN samples, their success is largely attributable to overfitting unstable
features such as frequency artifacts, which will cause failures when facing
unknown GANs or perturbation attacks. To overcome the issue, we propose a
robust detection framework based on a novel multi-view image completion
representation. The framework first learns various …
artifacts deepfakes defense detection features gan generated machine malicious representation synthesized work