2022
DOI: 10.1109/tcsvt.2021.3138795
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Concealed Attack for Robust Watermarking Based on Generative Model and Perceptual Loss

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Cited by 84 publications
(25 citation statements)
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“…Many image protection methods have been proposed, such as image hiding technology, image watermarking technology, and image encryption technology [ 7 , 8 , 9 , 10 , 11 ]. Among these image protection techniques, image encryption is the most direct way, which converts the original plaintext information into a noisy image.…”
Section: Introductionmentioning
confidence: 99%
“…Many image protection methods have been proposed, such as image hiding technology, image watermarking technology, and image encryption technology [ 7 , 8 , 9 , 10 , 11 ]. Among these image protection techniques, image encryption is the most direct way, which converts the original plaintext information into a noisy image.…”
Section: Introductionmentioning
confidence: 99%
“…As an important medium of information exchange, the image has become an important research object of scholars. Many methods are proposed to protect images [1][2][3][4], such as image hiding technology, zerowatermarking technology, and image encryption technology [5][6][7][8][9]. Image encryption technology is to convert plaintext into noise image; it is the most commonly used technology.…”
Section: Introductionmentioning
confidence: 99%
“…e drawback to these hand-crafted algorithms is that they are not simultaneously robust to some types of distortions because different types of distortions often require different techniques [8]. Consequently, some deep learning-based algorithms have been presented [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. ey usually utilize convolutional neural network (CNN) to design end-to-end architecture with an encoder and a decoder.…”
Section: Introductionmentioning
confidence: 99%
“…Mun et al [20] introduced attention mechanism into the watermarking field to achieve good performance in robustness against attacks. In addition, some notable algorithms with adversarial training [21][22][23] have greatly improved the perceptual quality of the watermarked images.…”
Section: Introductionmentioning
confidence: 99%