Facial Beauty Prediction and Analysis based on Deep Convolutional Neural Network: A Review

  • Jwan Saeed Duhok Polytechnic University, Iraq
  • Adnan Mohsin Abdulazeez Duhok Polytechnic University, Duhok, Kurdistan Region, IRAQ
Keywords: Facial beauty prediction, deep learning, convolutional neural network, transfer learning, generative adversarial networks.

Abstract

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.

Published
15-04-2021
How to Cite
Saeed, J., & Abdulazeez, A. M. (2021). Facial Beauty Prediction and Analysis based on Deep Convolutional Neural Network: A Review. Journal of Soft Computing and Data Mining, 2(1), 1-12. Retrieved from https://publisher.uthm.edu.my/ojs/index.php/jscdm/article/view/7878
Section
Articles