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ReDMark: Framework for Residual Diffusion Watermarking on Deep Networks
[article]
2018
arXiv
pre-print
Due to the rapid growth of machine learning tools and specifically deep networks in various computer vision and image processing areas, application of Convolutional Neural Networks for watermarking have recently emerged. In this paper, we propose a deep end-to-end diffusion watermarking framework (ReDMark) which can be adapted for any desired transform space. The framework is composed of two Fully Convolutional Neural Networks with the residual structure for embedding and extraction. The whole
arXiv:1810.07248v3
fatcat:nm5ozkz7abgy3kteuerdc4x6ou