一种利用年龄编辑改进年龄估计的方法

doi:10.12066/j.issn.1007-2861.2250

Abstract

Abstract:

As an emerging biometric identification technology, face age estimation is a classic learning problem in computer vision. Based on the powerful data generation ability of a generative adversarial network (GAN), a method to improve age estimation by using age editing is proposed. The training data suitable for age estimation were amplified by combining the training age editing network-StarGAN and the age estimation network-soft stagewise regression network (SSR-Net), in stages. Experimental results show that the method achieves the better age estimation results under unrestricted conditions.

Key words: age editing, age estimation, generative adversarial network (GAN), data amplification

CLC Number:

TP391.4

ZHANG Chenyu, XU Shugong, HUANG Jianbo. Method for improving age estimation using age editing[J]. Journal of Shanghai University（Natural Science Edition）, 2021, 27(1): 28-38.

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References 22

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Method for improving age estimation using age editing

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