OpenFace: A general-purpose face recognition library with mobile applications

1 Jan 2016  ·  Brandon Amos, Bartosz Ludwiczuk, Mahadev Satyanarayanan ·

Cameras are becoming ubiquitous in the Internet of Things (IoT) and can use face recognition technology to improve context. There is a large accuracy gap between today’s publicly available face recognition systems and the state-of-the-art private face recognition systems... This paper presents our OpenFace face recognition library that bridges this accuracy gap. We show that OpenFace provides near-human accuracy on the LFW benchmark and present a new classification benchmark for mobile scenarios. This paper is intended for non-experts interested in using OpenFace and provides a light introduction to the deep neural network techniques we use. read more

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Datasets


Task Dataset Model Metric Name Metric Value Global Rank Benchmark
Face Verification Labeled Faces in the Wild OpenFace Accuracy 92.92% # 27

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