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BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

Valentin Bazarevsky
Andrey Vakunov
CVPR Workshop on Computer Vision for Augmented and Virtual Reality 2019, IEEE, Long Beach, CA (2019)

Abstract

We present BlazeFace, a lightweight and well-performing face detector tailored for mobile GPU inference. It runs at a speed of 200--1000+ FPS on flagship devices. This super-realtime performance enables it to be applied to any augmented reality pipeline that requires an accurate facial region of interest as an input for task-specific models, such as 2D/3D facial keypoint or geometry estimation, facial features or expression classification, and face region segmentation. Our contributions include a lightweight feature extraction network inspired by, but distinct from MobileNetV1/V2, a GPU-friendly anchor scheme modified from Single Shot MultiBox Detector (SSD), and an improved tie resolution strategy alternative to non-maximum suppression.

Research Areas