论文标题
两个年龄合成和估计技术的概述
An Overview of Two Age Synthesis and Estimation Techniques
论文作者
论文摘要
年龄估计是一种从数字面部图像中预测人类年龄的技术，该技术可以根据年份的度量来分析一个人的面部图像并估算其年龄。如今，聪明的年龄估计和年龄综合已成为计算机视觉和面部验证系统中尤为普遍的研究主题。年龄合成的定义是在美学上呈现面部图像，并对人的脸产生复兴和自然的衰老影响。年龄估计的定义是为了将面部图像自动标记为年龄组（年范围）或人脸的确切年龄（年）。在此案例研究中，我们概述了与基于面部图像的年龄综合和估计主题有关的现有模型，流行技术，系统性能以及技术挑战。这篇综述的主要目标是通过系统的讨论来轻松理解和有希望的未来方向。
Age estimation is a technique for predicting human ages from digital facial images, which analyzes a person's face image and estimates his/her age based on the year measure. Nowadays, intelligent age estimation and age synthesis have become particularly prevalent research topics in computer vision and face verification systems. Age synthesis is defined to render a facial image aesthetically with rejuvenating and natural aging effects on the person's face. Age estimation is defined to label a facial image automatically with the age group (year range) or the exact age (year) of the person's face. In this case study, we overview the existing models, popular techniques, system performances, and technical challenges related to the facial image-based age synthesis and estimation topics. The main goal of this review is to provide an easy understanding and promising future directions with systematic discussions.
