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20192021
most citedCharacterizing the Variability in Face Recognition Accuracy Relative to Race

44 citations · 44 across the 2 of their papers we have counts for

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cs.CV2021

Does Face Recognition Error Echo Gender Classification Error?

Ying Qiu, Vítor Albiero, Michael C. King +1

This paper is the first to explore the question of whether images that are classified incorrectly by a face analytics algorithm (e.g., gender classification) are any more or less l…

cs.CV2020

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…

cs.CV2020

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…

cs.CV2019

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…

cs.CV201944 cited

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…