A leading-silence artifact in FakeAVCeleb and AV-Deepfake1M lets a trivial classifier separate real from fake, and an unsupervised alignment method trained only on real data avoids relying on this shortcut.
What makes fake images detectable? understanding prop- erties that generalize
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Circumventing shortcuts in audio-visual deepfake detection datasets with unsupervised learning
A leading-silence artifact in FakeAVCeleb and AV-Deepfake1M lets a trivial classifier separate real from fake, and an unsupervised alignment method trained only on real data avoids relying on this shortcut.