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Ideal Facial Proportions in Generative Artificial Intelligence: What Does Artificial Intelligence Consider an Attractive Face?

作者信息

Sridhar Sindhura, Laryea Richmond L, Vildibill Harry D, Sivam Sunthosh K

机构信息

Texas A&M University College of Medicine, Houston, Texas, USA.

Department of Otolaryngology, Head and Neck Surgery, Baylor College of Medicine, Houston, Texas, USA.

出版信息

Facial Plast Surg Aesthet Med. 2026 Mar 16:fpsam20250007. doi: 10.1089/fpsam.2025.0007.

DOI:10.1089/fpsam.2025.0007
PMID:40569636
Abstract

BACKGROUND

To investigate the facial proportions and physical characteristics deemed ideal and attractive by current popular generative artificial intelligence (AI) models.

METHODS

"Attractive" and "ideal" face images were generated using five text-to-image models. Facial proportions of the generated images were measured and compared with the neoclassical canons of facial thirds and fifths. Generated facial proportions were compared between AI models and classical facial proportions using analysis of variance and unpaired Student's -test, respectively.

RESULTS

The generated images included 28 (70%) female faces and 29 (75%) Caucasian faces. Mean generated horizontal proportions were 33.7%, 32.0%, and 34.3%. Mean generated vertical proportions were 21.1%, 18.0%, 21.1%, 17.9%, and 21.7%. The middle horizontal segment was significantly smaller in generated "ideal faces," and the lower horizontal segment was larger in generated "attractive faces" compared with classical proportions ( < 0.001 and = 0.01, respectively); the left and right middle vertical segments were significantly smaller in all generated faces compared with classical proportions ( < 0.001).

CONCLUSION

There are significant differences between the definition of attractive and ideal faces in generative AI models and classical facial proportions. These differences may reflect biases present within the models or may reflect changing cultural perceptions of facial attractiveness.

摘要

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