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arXiv:1907.05047cs.CV

BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs

Valentin Bazarevsky, Yury Kartynnik, Andrey Vakunov, Karthik Raveendran, Matthias Grundmann

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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.

arXiv comments
4 pages, 3 figures; CVPR Workshop on Computer Vision for Augmented and Virtual Reality, Long Beach, CA, USA, 2019
Journal reference
DOI
Subjects
cs.CVComputer Vision and Pattern Recognition

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    • There's also Blazeface: https://arxiv.org/abs/1907.05047, which the authors do not seem to mention.

      m0zgView on HNParent context

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