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

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


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.