Detecting and Simulating Artifacts in GAN Fake Images

15 Jul 2019 Xu Zhang Svebor Karaman Shih-Fu Chang

To detect GAN generated images, conventional supervised machine learning algorithms require collection of a number of real and fake images from the targeted GAN model. However, the specific model used by the attacker is often unavailable... (read more)

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