Visual Sentiment and Affective Computing Algorithms, Deep Learning-based Multimodal Emotion Recognition and Automated Digital Beauty Technologies, and 3D Machine Learning-based Facial Avatar Makeup Simulation and Generative Artificial Intelligence
Visual Sentiment and Affective Computing Algorithms, Deep Learning-based Multimodal Emotion Recognition and Automated Digital Beauty Technologies, and 3D Machine Learning-based Facial Avatar Makeup Simulation and Generative Artificial Intelligence
Author(s): Gheorghe H. Popescu, Ahmed Diaa Khamis, Vasily Erokhin, Silvia-Elena Iacob, Rudy Ujang, Dan Mihai BoajăSubject(s): Media studies, Individual Psychology, Social psychology and group interaction, Neuropsychology, Behaviorism, ICT Information and Communications Technologies
Published by: Addleton Academic Publishers
Keywords: visual sentiment; affective computing; emotion recognition; digital beauty; facial avatar makeup simulation; generative artificial intelligence virtual try-on;
Summary/Abstract: This paper draws on a substantial body of theoretical and empirical research on visual sentiment and affective computing algorithms, deep learningbased multimodal emotion recognition and automated digital beauty technologies, and 3D machine learning-based facial avatar makeup simulation and generative artificial intelligence virtual try-on tools for perceived social validation, unfavorable appearance comparisons, and negative body image, mood, and self-esteem. The review software systems leveraged for article screening and quality evaluation include AMSTAR, CADIMA, DistillerSR, Eppi-Reviewer, JBI SUMARI, Litstream, PICO Portal, and SWIFT-Active Screener. The case studies cover Airbrush, B612, BeautyPlus, Evoto, FaceApp, Facetune, Fotor, GlamAR, Perfect365, PortraitPro, PrettyUp, SODA, Ulike, Vivid Glam, Wondershare DemoCreator, and YouCam.
Journal: Journal of Research in Gender Studies
- Issue Year: 15/2025
- Issue No: 2
- Page Range: 65-75
- Page Count: 11
- Language: English
- Content File-PDF
