Augmented Reality Application for Makeup Style Transfer: A Bibliometric Study
DOI:
https://doi.org/10.12928/joves.v9i1.13746Keywords:
Augmented Reality, Makeup Style Transfer, Bibliometric, Generative Adversarial Networks, Cosmetology EducationAbstract
This study examines the development and trends in the use of Augmented Reality (AR) technology applied to makeup style transfer through a bibliometric approach. Using publication data from the Scopus database covering the period from 2013 to 2025, a bibliometric analysis was conducted to map the growth of scientific literature in this field. The results reveal a significant increase in the number of publications, particularly in recent years, indicating a growing research interest. Key contributing authors, journals, and countries were successfully identified, with notable cross-institutional and cross-regional collaborations. The findings also highlight that deep learning methods—especially Generative Adversarial Networks (GANs)—have emerged as the dominant technology in makeup style transfer research, driving progress in the development of realistic and efficient virtual makeup applications. This study underscores the potential of AR as a major innovation in beauty education and practice, offering interactive and personalized learning experiences. Future research is recommended to focus on the development of more accurate and accessible AR technologies to support the ongoing advancement of the beauty industry.
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