Thank you for giving me the chance to share my message, and I hope everyone remembers how much they are worth. Face2Face: Real-Time Face Capture and Reenactment of RGB Videos pdf icon hmtl icon Justus Thies, Michael Zollhfer, Marc Stamminger, Christian Theobalt. Face2Face: Real-time face capture and reenactment of rgb videos. I want to thank everyone who came to support, as well as the wonderful UBSS board who was by my side every step of the way. We present a novel approach for real-time facial reenactment of a monocular target video sequence (e.g., Youtube video). A webcam-enabled application is also provided that translates your face to the trained face in real-time. The fact that I was able to stand up and deliver a message that I hold so close to my heart was truly inspiring, and hopefully I was able to offer some kind of inspiration to everybody else in the room as well.ĭespite the the arduous nature of planning this event, the learning experience that came with it and seeing the outcome of the event play out right in front of my eyes made everything absolutely worth it. This is a pix2pix demo that learns from facial landmarks and translates this into a face. Face2Face: Real-Time Face Capture and Reenactment of RGB Videos A morphable model for the synthesis of 3D faces Volker Blanz Thomas Vetter Deformation. This year I centered the event around the message "Know Your Worth," a topic that I found myself extremely attached to as it pertains to the self-doubt and confidence issues that I struggle with in my life.īut being given the chance to speak to so many people, specifically the young women in the room, instilled a confidence in me I didn't realize I had. Last night I was able to host the United Business Student Senate's fourth annual Galentine's Day, an event that encourages female empowerment in the professional workforce. Face2Face is introduced, the first R eal-time H igh-resolution and O ne-shot (RHO, ) face reenactment framework which consists of two fast and efficient sub-networks, and can produce results of equal or better visual quality, yet with significantly less time and memory overhead. From Justus Thies, Michael Zollhfer, Marc Stamminger, Christian Theobalt and Matthias Niener: We present a novel approach for real-time facial reenactment.
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