Unconstrained face verification using deep CNN features

Jun-Cheng Chen,Rama Chellappa,Vishal M Patel

doi:10.1109/wacv.2016.7477557

Unconstrained face verification using deep CNN features

Jun-Cheng Chen, Rama Chellappa + Show 1 more

Open Access

https://doi.org/10.1109/wacv.2016.7477557

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Publication Date: Mar 1, 2016

Citations: 254

Affiliation: University of Maryland, College Park, Rutgers, The State University of New Jersey

#Labeled Face In The Wild #IARPA Janus Benchmark A + Show 8 more

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Abstract

In this paper, we present an algorithm for unconstrained face verification based on deep convolutional features and evaluate it on the newly released IARPA Janus Benchmark A (IJB-A) dataset as well as on the traditional Labeled Face in the Wild (LFW) dataset. The IJB-A dataset includes real-world unconstrained faces from 500 subjects with full pose and illumination variations which are much harder than the LFW and Youtube Face (YTF) datasets. The deep convolutional neural network (DCNN) is trained using the CASIA-WebFace dataset. Results of experimental evaluations on the IJB-A and the LFW datasets are provided.

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