English

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

Computer Vision and Pattern Recognition 2019-07-17 v1

Abstract

We present an end-to-end neural network-based model for inferring an 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.

Keywords

Cite

@article{arxiv.1907.06724,
  title  = {Real-time Facial Surface Geometry from Monocular Video on Mobile GPUs},
  author = {Yury Kartynnik and Artsiom Ablavatski and Ivan Grishchenko and Matthias Grundmann},
  journal= {arXiv preprint arXiv:1907.06724},
  year   = {2019}
}

Comments

4 pages, 4 figures; CVPR Workshop on Computer Vision for Augmented and Virtual Reality, Long Beach, CA, USA, 2019