FAME, a 2.61M-parameter VGG-19 plus attention LSTM network, attributes face-swap deepfake videos to their generating models with reported accuracies of 79.7% on DFDM, 97.5% on FF++, and 96.8% on FakeAVCeleb.
Is space-time attention all you need for video understanding? In Proceedings of the International Conference on Machine Learning (ICML), pages 813–824
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FAME: A Lightweight Spatio-Temporal Network for Model Attribution of Face-Swap Deepfakes
FAME, a 2.61M-parameter VGG-19 plus attention LSTM network, attributes face-swap deepfake videos to their generating models with reported accuracies of 79.7% on DFDM, 97.5% on FF++, and 96.8% on FakeAVCeleb.