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

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

15 Jul 2019arXiv:1907.06724archive 2025-07-28

Yury Kartynnik, Artsiom Ablavatski, Ivan Grishchenko, Matthias Grundmann

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.

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Neilblaze/Adoptic mentioned on GitHubtfMIT report
thepowerfuldeez/facemesh.pytorch mentioned on GitHubpytorchApache-2.0 report

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create_facenet gouthamvgk/facemesh_coreml_tf/convert_facemesh.py community (archive-listed) unverified Apache-2.0 (permissive) · f122fb567b550ad7 · report
create_letterbox_image gouthamvgk/facemesh_coreml_tf/utils.py community (archive-listed) unverified Apache-2.0 (permissive) · 10f4241f60b3005f · report
down_sampling gouthamvgk/facemesh_coreml_tf/layers.py community (archive-listed) unverified Apache-2.0 (permissive) · 6d2ce78e8f8e9ca1 · report
face_block gouthamvgk/facemesh_coreml_tf/layers.py community (archive-listed) unverified Apache-2.0 (permissive) · 3837021c116f17e1 · report
get_clean_name gouthamvgk/facemesh_coreml_tf/utils.py community (archive-listed) unverified Apache-2.0 (permissive) · ccfa6be5c82a6220 · report
res_block gouthamvgk/facemesh_coreml_tf/layers.py community (archive-listed) unverified Apache-2.0 (permissive) · 8ea50af8f581ca04 · report
xywh_to_tlbr gouthamvgk/facemesh_coreml_tf/utils.py community (archive-listed) unverified Apache-2.0 (permissive) · 7690736c43f51e7b · report

Tasks

Face Reconstruction

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Methods

SPEED

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