185 citations · 203 across the 6 of their papers we have counts for
6 papers
CMFDFormer: Transformer-based Copy-Move Forgery Detection with Continual Learning
Yaqi Liu, Chao Xia, Song Xiao +4
Copy-move forgery detection aims at detecting duplicated regions in a suspected forged image, and deep learning based copy-move forgery detection methods are in the ascendant. Thes…
Adaptive Spatial Steganography Based on Probability-Controlled Adversarial Examples
Sai Ma, Qingxiao Guan, Xianfeng Zhao +1
Explanation from Sai Ma: The experiments in this paper are conducted on Caffe framework. In Caffe, there is an API to directly set the gradient in Matlab. I wrongly use it to contr…
Weakening the Detecting Capability of CNN-based Steganalysis
Sai Ma, Qingxiao Guan, Xianfeng Zhao +1
Recently, the application of deep learning in steganalysis has drawn many researchers' attention. Most of the proposed steganalytic deep learning models are derived from neural net…
Copy-move Forgery Detection based on Convolutional Kernel Network
Yaqi Liu, Qingxiao Guan, Xianfeng Zhao
In this paper, a copy-move forgery detection method based on Convolutional Kernel Network is proposed. Different from methods based on conventional hand-crafted features, Convoluti…
Further Study on GFR Features for JPEG Steganalysis
Xia Chao, Guan Qingxiao, Zhao Xianfeng
The GFR (Gabor Filter Residual) features, built as histograms of quantized residuals obtained with 2D Gabor filters, can achieve competitive detection performance against adaptive…
Image Forgery Localization Based on Multi-Scale Convolutional Neural Networks
Yaqi Liu, Qingxiao Guan, Xianfeng Zhao +1
In this paper, we propose to utilize Convolutional Neural Networks (CNNs) and the segmentation-based multi-scale analysis to locate tampered areas in digital images. First, to deal…