290 citations · 1k across the 19 of their papers we have counts for
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Universal Deep Network for Steganalysis of Color Image based on Channel Representation
Kangkang Wei, Weiqi Luo, Shunquan Tan +1
Up to now, most existing steganalytic methods are designed for grayscale images, and they are not suitable for color images that are widely used in current social networks. In this…
Self-Adversarial Training incorporating Forgery Attention for Image Forgery Localization
Long Zhuo, Shunquan Tan, Bin Li +1
Image editing techniques enable people to modify the content of an image without leaving visual traces and thus may cause serious security risks. Hence the detection and localizati…
MCTSteg: A Monte Carlo Tree Search-based Reinforcement Learning Framework for Universal Non-additive Steganography
Xianbo Mo, Shunquan Tan, Bin Li +1
Recent research has shown that non-additive image steganographic frameworks effectively improve security performance through adjusting distortion distribution. However, as far as w…
Image Steganography based on Iteratively Adversarial Samples of A Synchronized-directions Sub-image
Xinghong Qin, Shunquan Tan, Bin Li +2
Nowadays a steganography has to face challenges of both feature based staganalysis and convolutional neural network (CNN) based steganalysis. In this paper, we present a novel steg…