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2019

BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

Bazarevsky, Valentin, Kartynnik, Yury, Vakunov, Andrey et al.

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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.

BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs · Around

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The pascal visual object classes (VOC) challenge
Mark Everingham, Luc Gool, Christopher K. Williams, John Winn, and Andrew Zisserman · 2010
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Fast R-CNN
Ross Girshick · 2015
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Faster R-CNN: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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