Journal
WWW'20: COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2020
Volume -, Issue -, Pages 88-89Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3366424.3382711
Keywords
Deepfake videos; Tampering detection; Multi-task learning
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In this paper, we propose a novel Patch&Pair Convolutional Neural Networks (PPCNN) to distinguish Deepfake videos or images from real ones. Through the comprehensive evaluations on public datasets, we demonstrate that our model performs better than existing detection methods and show better generalization.
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