CycleGAN, a Master of Steganography

8 Dec 2017 Casey Chu Andrey Zhmoginov Mark Sandler

CycleGAN (Zhu et al. 2017) is one recent successful approach to learn a transformation between two image distributions. In a series of experiments, we demonstrate an intriguing property of the model: CycleGAN learns to "hide" information about a source image into the images it generates in a nearly imperceptible, high-frequency signal... (read more)

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