Pixel Codec Avatars

Conference on Computer Vision and Pattern Recognition (CVPR)


Telecommunication with photorealistic avatars in virtual or augmented reality is a promising path for achieving authentic face-to-face communication in 3D over remote physical distances. In this work, we present the Pixel Codec Avatars (PiCA): a deep generative model of 3D human faces that achieves state of the art reconstruction performance while being computationally efficient and adaptive to the rendering conditions during execution. Our model combines two core ideas: (1) a fully convolutional architecture for decoding spatially varying features, and (2) a rendering-adaptive per-pixel decoder. Both techniques are integrated via a dense surface representation that is learned in a weakly-supervised manner from low-topology mesh tracking over training images. We demonstrate that PiCA improves reconstruction over existing techniques across testing expressions and views on persons of different gender and skin tone. Importantly, we show that the PiCA model is much smaller than the state-of-art baseline model, and makes multi-person telecommunication possible: on a single Oculus Quest 2 mobile VR headset, 5 avatars are rendered in realtime in the same scene.


Related Publications

All Publications

ICML - July 24, 2021

Using Bifurcations for Diversity in Differentiable Games

Jonathan Lorraine, Jack Parker-Holder, Paul Vicol, Aldo Pacchiano, Luke Metz, Tal Kachman, Jakob Foerster

IEEE WHC - July 6, 2021

Hasti: Haptic and Audio Synthesis for Texture Interactions

Sonny Chan, Chase Tymms, Nicholas Colonnese

UAI - July 23, 2021

High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces

David Eriksson, Martin Jankowiak

The Journal of the Acoustical Society of America - February 4, 2021

Perceptual implications of different Ambisonics-based methods for binaural reverberation

Isaac Engel, Craig Henry, Sebastià V. Amengual Garí, Philip W. Robinson, Lorenzo Picinali

To help personalize content, tailor and measure ads, and provide a safer experience, we use cookies. By clicking or navigating the site, you agree to allow our collection of information on and off Facebook through cookies. Learn more, including about available controls: Cookies Policy