2 citations · 3 across the 3 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…