44 citations · 44 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…
The Criminality From Face Illusion
Kevin W. Bowyer, Michael King, Walter Scheirer +1
The automatic analysis of face images can generate predictions about a person's gender, age, race, facial expression, body mass index, and various other indices and conditions. A f…
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…
Does Face Recognition Accuracy Get Better With Age? Deep Face Matchers Say No
Vítor Albiero, Kevin W. Bowyer, Kushal Vangara +1
Previous studies generally agree that face recognition accuracy is higher for older persons than for younger persons. But most previous studies were before the wave of deep learnin…
Characterizing the Variability in Face Recognition Accuracy Relative to Race
KS Krishnapriya, Kushal Vangara, Michael C. King +2
Many recent news headlines have labeled face recognition technology as biased or racist. We report on a methodical investigation into differences in face recognition accuracy betwe…