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

Jwan Najeeb Saeed, Adnan Mohsin Abdulazeez

2021Journal of Soft Computing and Data Mining51 citationsDOIOpen Access PDF

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 comparisonsbetween 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.

Topics & Concepts

BeautyConvolutional neural networkComputer scienceArtificial intelligenceFace (sociological concept)Deep learningFeature (linguistics)Representation (politics)Convolution (computer science)Facial recognition systemArtificial neural networkPattern recognition (psychology)AestheticsArtSocial scienceLawSociologyPoliticsPolitical sciencePhilosophyLinguisticsFace recognition and analysisEvolutionary Psychology and Human BehaviorGenerative Adversarial Networks and Image Synthesis
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