185 citations · 263 across the 9 of their papers we have counts for
9 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…
TBFormer: Two-Branch Transformer for Image Forgery Localization
Yaqi Liu, Binbin Lv, Xin Jin +2
Image forgery localization aims to identify forged regions by capturing subtle traces from high-quality discriminative features. In this paper, we propose a Transformer-style netwo…
GAN-based Medical Image Small Region Forgery Detection via a Two-Stage Cascade Framework
Jianyi Zhang, Xuanxi Huang, Yaqi Liu +2
Using generative adversarial network (GAN)\cite{RN90} for data enhancement of medical images is significantly helpful for many computer-aided diagnosis (CAD) tasks. A new attack ca…
Two-Stage Copy-Move Forgery Detection with Self Deep Matching and Proposal SuperGlue
Yaqi Liu, Chao Xia, Xiaobin Zhu +1
Copy-move forgery detection identifies a tampered image by detecting pasted and source regions in the same image. In this paper, we propose a novel two-stage framework specially fo…
Adversarial Learning for Image Forensics Deep Matching with Atrous Convolution
Yaqi Liu, Xianfeng Zhao, Xiaobin Zhu +1
Constrained image splicing detection and localization (CISDL) is a newly proposed challenging task for image forensics, which investigates two input suspected images and identifies…
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…
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…