Capturing variability in children's faces: an artificial, yet realistic, face stimulus set.

ABSTRACT: Children's faces are underrepresented in face databases, and existing databases that do focus on children tend to have limitations in terms of the number of faces available and the diversity of ages and ethnicities represented. To improve the availability of children's faces for experimental research purposes, we created a novel face database that contains 500 artificial images of children that are diverse in terms of both age (ages 3 to 10) and ethnicity (representing 15 different racial or ethnic groups). Using deep neural networks, we produced a large collection of synthetic photographs that look like naturalistic, realistic faces of children. To assess the representativeness of the dataset, adult participants (N = 585) judged the age, gender, ethnicity, and emotion of artificial

SUBMITTER: Thierry SM 

PROVIDER: S-EPMC12439430 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature