Google Research

Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs

CVPR Workshop on Computer Vision for Augmented and Virtual Reality 2019, IEEE, Long Beach, CA

Abstract

We present an end-to-end neural network-based model for inferring the approximate 3D mesh representation of a human face from single camera input for AR applications. The relatively dense mesh model of 468 vertices is well-suited for face-based AR effects. The proposed model demonstrates super-realtime inference speed on mobile GPUs (100--1000+ FPS, depending on the device and model variant) and a high prediction quality that is comparable to the variance in manual annotations of the same image.

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