Recurrent-Convolution Approach to DeepFake Detection - State-Of-Art Results on FaceForensics++

05/02/2019

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by   Ekraam Sabir, et al.

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Spread of misinformation has become a significant problem, raising the importance of relevant detection methods. While there are different manifestations of misinformation, in this work we focus on detecting face manipulations in videos. Specifically, we attempt to detect Deepfake, Face2Face and FaceSwap manipulations in videos. We exploit the temporal dynamics of videos with a recurrent approach. Evaluation is done on FaceForensics++ dataset and our method improves upon the previous state-of-the-art up to 4.55