56 citations · 58 across the 3 of their papers we have counts for
5 papers
Exploring Causes of Demographic Variations In Face Recognition Accuracy
Gabriella Pangelinan, K. S. Krishnapriya, Vitor Albiero +5
In recent years, media reports have called out bias and racism in face recognition technology. We review experimental results exploring several speculated causes for asymmetric cro…
Gendered Differences in Face Recognition Accuracy Explained by Hairstyles, Makeup, and Facial Morphology
Vítor Albiero, Kai Zhang, Michael C. King +1
Media reports have accused face recognition of being ''biased'', ''sexist'' and ''racist''. There is consensus in the research literature that face recognition accuracy is lower fo…
A Method for Curation of Web-Scraped Face Image Datasets
Kai Zhang, Vítor Albiero, Kevin W. Bowyer
Web-scraped, in-the-wild datasets have become the norm in face recognition research. The numbers of subjects and images acquired in web-scraped datasets are usually very large, wit…
How Does Gender Balance In Training Data Affect Face Recognition Accuracy?
Vítor Albiero, Kai Zhang, Kevin W. Bowyer
Deep learning methods have greatly increased the accuracy of face recognition, but an old problem still persists: accuracy is usually higher for men than women. It is often specula…
Analysis of Gender Inequality In Face Recognition Accuracy
Vítor Albiero, Krishnapriya K. S., Kushal Vangara +3
We present a comprehensive analysis of how and why face recognition accuracy differs between men and women. We show that accuracy is lower for women due to the combination of (1) t…