Open AccessComputer Science

J. Saeed, A. Abdulazeez

2021.4.15Journal of Soft Computing and Data Mining

DOI: 10.30880/jscdm.2021.02.01.001

tlooto Summary

This article reviewed the recent research on computer prediction and analysis of face beauty based on deep convolution neural network DCNN and provided possible lines of research and challenges that can help researchers in advancing the state of the art in future work.

Abstract

Facial attractiveness or facial beauty prediction (FBP) is a current study that has several potential usages. It is a key difficulty area in the computer vision domain because of the few public databases related to FBP and its experimental trials on the minor-scale database. Moreover, the evaluation of facial beauty is personalized in nature, with people having personalized favor of beauty. Deep learning techniques have displayed a significant ability in terms of analysis and feature representation. The previous studies focussed on scattered portions of facial beauty with fewer comparisons between diverse techniques. Thus, this article reviewed the recent research on computer prediction and analysis of face beauty based on deep convolution neural network DCNN. Furthermore, the provided possible lines of research and challenges in this article can help researchers in advancing the state – of- art in future work.

Citation format

SAEED, J.; ABDULAZEEZ, A. Facial beauty prediction and analysis based on deep convolutional neural network: A review. Journal of Soft Computing and Data Mining, 2021.