A Progressive Learning Framework for Unconstrained Face Recognition

被引：0
|
作者：
Chai, Zhenhua [1 ]
Li, Shengxi [1 ]
Meng, Huanhuan [1 ]
Lai, Shenqi [1 ]
Wei, Xiaoming [1 ]
Zhang, Jianwei [1 ]
机构：
[1] Vison & Image Ctr VIC Meituan, Beijing, Peoples R China
来源：
2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW) | 2019年
关键词：
MARGIN SOFTMAX;
D O I：
10.1109/ICCVW.2019.00331
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The carefully designed backbone network, the increase of training data and the improved training skills have boosted the performance of modern face recognition systems. However, in some deployment cases which aim at model compactness and energy efficiency, some of the existing systems may fail due to the high complexity. Lightweight Face Recognition Challenge is proposed in order to make some progress in this direction and establishes a new comprehensive benchmark. In this challenge, we have designed a light weight backbone architecture and all the parameters are trained in a progressive way. Finally we achieve the 5th in track 1 and the 4th in track 3.
引用
收藏
页码：2703 / 2710
页数：8
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