“Demo of Face2Face: Real-Time Face Capture and Reenactment of RGB Videos” by Thies, Zollhöfer, Stamminger, Theobalt and Nießner

  • ©Justus Thies, Michael Zollhöfer, Marc Stamminger, Christian Theobalt, and Matthias Nießner

  • ©Justus Thies, Michael Zollhöfer, Marc Stamminger, Christian Theobalt, and Matthias Nießner

Title:


    Demo of Face2Face: Real-Time Face Capture and Reenactment of RGB Videos

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Entry Number: 05


Description:


    We present 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. Our goal is to animate the facial expressions of the target video by a source actor and re-render the manipulated output video in a photo-realistic fashion. To this end, we first address the under-constrained problem of facial identity recovery from monocular video by non-rigid model-based bundling. At run time, we track facial expressions of both source and target video using a dense photometric consistency measure. Reenactment is then achieved by fast and efficient deformation transfer between source and target. The mouth interior that best matches the re-targeted expression is retrieved from the target sequence and warped to pro- duce an accurate fit. Finally, we convincingly re-render the synthesized target face on top of the corresponding video stream such that it seamlessly blends with the real-world illumination. We demonstrate our method in a live setup, where Youtube videos are reenacted in real time.


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References:


    THIES, J., ZOLLHÖFER, M., STAMMINGER, M., THEOBALT, C., AND NIESSNER, M. 2016. Face2Face: Real-time Face Capture and Reenactment of RGB Videos. In Proc. CVPR 2016.


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