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



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


No methods listed for this paper. Add relevant methods here