VIPLFaceNet: an open source deep face recognition SDK

doi:10.1007/s11704-016-6076-3

Front. Comput. Sci.

2017, Vol. 11

Issue (2) : 208-218 https://doi.org/10.1007/s11704-016-6076-3

RESEARCH ARTICLE

VIPLFaceNet: an open source deep face recognition SDK

Xin LIU^1,²,Meina KAN^1,²,Wanglong WU^1,²,Shiguang SHAN^1,²(

),Xilin CHEN^1,²

¹. Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing 100190, China
². University of Chinese Academy of Sciences, Beijing 100049, China

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Abstract

Robust face representation is imperative to highly accurate face recognition. In this work, we propose an open source face recognition method with deep representation named as VIPLFaceNet, which is a 10-layer deep convolutional neural network with seven convolutional layers and three fully-connected layers. Compared with the well-known AlexNet, our VIPLFaceNet takes only 20% training time and 60% testing time, but achieves 40% drop in error rate on the real-world face recognition benchmark LFW. Our VIPLFaceNet achieves 98.60% mean accuracy on LFW using one single network. An open-source C++ SDK based on VIPLFaceNet is released under BSD license. The SDK takes about 150ms to process one face image in a single thread on an i7 desktop CPU. VIPLFaceNet provides a state-of-the-art start point for both academic and industrial face recognition applications.

Keywords deep learning face recognition open source VIPLFaceNet

Corresponding Author(s): Shiguang SHAN

Just Accepted Date: 30 September 2016 Online First Date: 17 March 2017 Issue Date: 06 April 2017

Cite this article:

Xin LIU,Meina KAN,Wanglong WU, et al. VIPLFaceNet: an open source deep face recognition SDK[J]. Front. Comput. Sci., 2017, 11(2): 208-218.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-016-6076-3
https://academic.hep.com.cn/fcs/EN/Y2017/V11/I2/208

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