International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Facial Aging Prediction Challenges and Developments: A Review

Amina Taha ALazaweComputer Science Department, College of Computer Science and Mathematics, University of Mosul, Nineveh, IraqYusra Faisal MohammadComputer Science Department, College of Education for Pure Science, University of Mosul, Nineveh, Iraq

Vol 9 No 4 (2025): Volume 9, Issue 4, April 2025 | Pages: 33-49

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 11-04-2025

doi Logo doi.org/10.47001/IRJIET/2025.904006

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Abstract

Our world today is full of development and people have become obsessed with beauty and maintaining the continuity of youth and fear of facial aging, which represents gradual changes in physiological functions. Hence, the need to simulate facial aging has emerged. Recently, many contributions have spread that have addressed this phenomenon. In this paper, we highlight many facial aging methodologies: the traditional approach, the deep learning approach, and the hybrid model approach. Regarding the feature-based approach, we will explain its strengths and weaknesses. Then we will highlight the methodologies based on deep learning, especially the competitive generative networks that have improved the accuracy and realism of facial aging images. We will also explain the strengths, weaknesses, and possible improvement. In addition, we will mention the hybrid models and their strengths and weaknesses. The datasets used in this work are presented. Furthermore, we will explain how to deal with the challenges associated with facial aging estimation, starting with the obstacles that accompany the dataset, warnings about privacy and ethical considerations, with the need to address these challenges to ensure the safe and ethical use of the techniques, and discuss the impact of the unbalanced distribution of the dataset, and touch on some of the criteria for evaluating these methods. Finally, we present a future vision on the emerging trends, challenges and future directions in the field of facial aging in order to help guide future research in the right direction.

Keywords

Age Progression, Conditional Attention Normalization (CAN), Facial aging estimation Generative Adversarial Networks (GANS, Enhanced Super-resolution Generative Adversarial Network (ESRGAN)


Citation of this Article

Amina Taha ALazawe, & Yusra Faisal Mohammad. (2025). Facial Aging Prediction Challenges and Developments: A Review. International Research Journal of Innovations in Engineering and Technology - IRJIET, 9(4), 33-49. Article DOI https://doi.org/10.47001/IRJIET/2025.904006

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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