Multi-sensory Perception and Deep Learning-based Virtual Try-on Technologies for Body Shape and Attractiveness, Unrealistic Societal Beauty Standards, and Thinness Ideal Internalization
Multi-sensory Perception and Deep Learning-based Virtual Try-on Technologies for Body Shape and Attractiveness, Unrealistic Societal Beauty Standards, and Thinness Ideal Internalization

Summary/Abstract: This article reviews and advances existing literature concerning artificial intelligence-generated hyper-realistic body-inclusive avatars, photoshopped and filtered images, and beauty apps and filters. In this research, previous findings were cumulated showing that 3D digital clothing technologies, wearable artificial intelligence devices, and beauty filter algorithms configure body shape and attractiveness, unrealistic societal beauty standards, and thinness ideal internalization. Throughout June 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “body shape and attractiveness,” “unrealistic societal beauty standards,” and “thinness ideal internalization” + “multi-sensory perception and deep learning-based virtual try-on technologies.” As research published between 2019 and 2022 was inspected, only 169 articles satisfied the eligibility criteria, and 26 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AXIS, MMAT, ROBIS, and SRDR.

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