Facial Age Estimation using Deep neural networks: A Survey

Abstract

Facial age estimation techniques are extensively used in vitality applications nowadays; however, they are a time-consuming task. Compared to other methods, deep learning algorithms showed a superior performance to solve face related age estimation problem. The current surveys are incomplete, not up-to-date and are not concerned with deep learning in particular. In this paper, a comprehensive updated summary of the deep age estimation frameworks are introduced. We review the previous research efforts in deep age estimation systems and present the popular datasets. Convolution Neural Networks (CNN) are introduced with their models. The performance criteria widely used in evaluation are declared. Finally, the challenges and the future directions are discussed to reach a robust facial age estimation system.