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Resampling is an important signature of manipulated images. In this paper, we propose two methods to detect and localize image manipulations based on a combination of resampling features and deep learning. In the first method, the Radon transform of resampling features are computed on overlapping image patches. Deep learning classifiers and a Gaussian conditional random field model are then used to create a heatmap. Tampered regions are located using a Random Walker segmentation method. In thedoi:10.1109/cvprw.2017.235 dblp:conf/cvpr/BunkBMNFMCRP17 fatcat:twryuybkanbmvplqiqm7kfmrki