Face2Face: Real-time Face Capture and Reenactment of RGB Videos

Conference contribution


Publication Details

Author(s): Thies J, Zollhöfer M, Stamminger M, Theobald C, Nießner M
Publication year: 2016
Conference Proceedings Title: Proc. Computer Vision and Pattern Recognition (CVPR)
Pages range: 2387-2395


Abstract


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 produce 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.


FAU Authors / FAU Editors

Nießner, Matthias
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)
Stamminger, Marc Prof. Dr.
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)
Thies, Justus
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)
Zollhöfer, Michael
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)


Research Fields

Geometric Modeling and 3D Reconstruction
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)


How to cite

APA:
Thies, J., Zollhöfer, M., Stamminger, M., Theobald, C., & Nießner, M. (2016). Face2Face: Real-time Face Capture and Reenactment of RGB Videos. In Proc. Computer Vision and Pattern Recognition (CVPR) (pp. 2387-2395). Las Vegas.

MLA:
Thies, Justus, et al. "Face2Face: Real-time Face Capture and Reenactment of RGB Videos." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas 2016. 2387-2395.

BibTeX: 

Last updated on 2019-22-07 at 07:35