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Image Copy-Move Forgery Detection via Deep PatchMatch and Pairwise Ranking Learning
April 29, 2024, 4:45 a.m. | Yuanman Li, Yingjie He, Changsheng Chen, Li Dong, Bin Li, Jiantao Zhou, Xia Li
cs.CV updates on arXiv.org arxiv.org
Abstract: Recent advances in deep learning algorithms have shown impressive progress in image copy-move forgery detection (CMFD). However, these algorithms lack generalizability in practical scenarios where the copied regions are not present in the training images, or the cloned regions are part of the background. Additionally, these algorithms utilize convolution operations to distinguish source and target regions, leading to unsatisfactory results when the target regions blend well with the background. To address these limitations, this study …
abstract advances algorithms arxiv copy cs.cv deep learning deep learning algorithms detection forgery however image images part practical progress ranking training type via
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