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Deepfake Caricatures: Amplifying attention to artifacts increases deepfake detection by humans and machines
[article]
2022
arXiv
pre-print
Deepfakes pose a serious threat to our digital society by fueling the spread of misinformation. It is essential to develop techniques that both detect them, and effectively alert the human user to their presence. Here, we introduce a novel deepfake detection framework that meets both of these needs. Our approach learns to generate attention maps of video artifacts, semi-supervised on human annotations. These maps make two contributions. First, they improve the accuracy and generalizability of a
arXiv:2206.00535v2
fatcat:7ph6ou2vufamfnvbricxc4c6su