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arXiv · 1609.03892

VIPLFaceNet: An Open Source Deep Face Recognition SDK

Xin Liu·Meina Kan·Wanglong Wu·Shiguang Shan·Xilin Chen
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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 7 convolutional layers and 3 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.

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Xin Liu, Meina Kan, Wanglong Wu, Shiguang Shan, Xilin Chen. 2016-09-13. VIPLFaceNet: An Open Source Deep Face Recognition SDK. https://arxiv.org/abs/1609.03892

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