{"title":"A generated image repository of aging faces.","authors":"Anna Pot, Laura L Carstensen","doi":"10.1038/s41597-025-05909-6","DOIUrl":null,"url":null,"abstract":"<p><p>Faces are a rich source of information for humans and a substantial amount of behavioral science research uses face stimuli to assess person perception. Unfortunately, this body of research is limited by an overreliance on young, predominantly white faces normed on young adult perceivers. To address these limitations, we created an open-access database of AI-generated faces that represents the same individuals at three life stages (young adulthood, middle age, and older adulthood) including equal numbers of males and females. Using advanced generative algorithms, the approach digitally aged 62 young individuals, thus preserving identity-specific features while realistically portraying age-related changes. The resulting database comprises 186 images. Each image has been age-normed and validated for authenticity. Although the database will be useful for many research questions, the stimuli are especially well-suited for research on age comparisons because the same individuals can be presented at different ages.</p>","PeriodicalId":21597,"journal":{"name":"Scientific Data","volume":"12 1","pages":"1610"},"PeriodicalIF":6.9000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12489049/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Data","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41597-025-05909-6","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Faces are a rich source of information for humans and a substantial amount of behavioral science research uses face stimuli to assess person perception. Unfortunately, this body of research is limited by an overreliance on young, predominantly white faces normed on young adult perceivers. To address these limitations, we created an open-access database of AI-generated faces that represents the same individuals at three life stages (young adulthood, middle age, and older adulthood) including equal numbers of males and females. Using advanced generative algorithms, the approach digitally aged 62 young individuals, thus preserving identity-specific features while realistically portraying age-related changes. The resulting database comprises 186 images. Each image has been age-normed and validated for authenticity. Although the database will be useful for many research questions, the stimuli are especially well-suited for research on age comparisons because the same individuals can be presented at different ages.
期刊介绍：
Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data.
The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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