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Jul 29, 2020 · We present Face2Face, a novel approach for real-time facial reenactment of a monocular target video sequence (e.g., Youtube video). The source sequence is also a monocular video stream, captured live with a commodity webcam.
Training data. Our framework relies on a large video dataset containing many identities, such as VoxCeleb. For each video frame, the following data is required: face mask (optional): the face area mask (can be generated by any face parsing methods, such as BiSeNet ).
In this paper, we employ a new dense markerless fa- cial performance capture method based on monocular RGB data, similar to state-of-the-art methods. However, instead of transferring facial expressions to virtual CG characters, our main contribution is monocular facial reenactment in real-time.
