“Demo of Face2Face: Real-Time Face Capture and Reenactment of RGB Videos” by Thies, Zollhöfer, Stamminger, Theobalt and Nießner
Conference:
Type(s):
E-Tech Type(s):
- Beyond Categorization
Entry Number: 05
Title:
- Demo of Face2Face: Real-Time Face Capture and Reenactment of RGB Videos
Presenter(s):
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.
Other Information:
To listen to the audio guide of this contribution in multiple other languages, visit: SIGGRAPH 2016 Emerging Technologies Audio Guides
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.
Keyword(s):
- face capture
- facial reenactment
- expression transfer
