56 citations · 107 across the 9 of their papers we have counts for
12 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 Gender Gap in Face Recognition Accuracy Is a Hairy Problem
Aman Bhatta, Vítor Albiero, Kevin W. Bowyer +1
It is broadly accepted that there is a "gender gap" in face recognition accuracy, with females having higher false match and false non-match rates. However, relatively little is kn…
Face Recognition Accuracy Across Demographics: Shining a Light Into the Problem
Haiyu Wu, Vítor Albiero, K. S. Krishnapriya +2
We explore varying face recognition accuracy across demographic groups as a phenomenon partly caused by differences in face illumination. We observe that for a common operational s…
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…
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…
Is Face Recognition Sexist? No, Gendered Hairstyles and Biology Are
Vítor Albiero, Kevin W. Bowyer
Recent news articles have accused face recognition of being "biased", "sexist" or "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…
Identity Document to Selfie Face Matching Across Adolescence
Vítor Albiero, Nisha Srinivas, Esteban Villalobos +5
Matching live images (``selfies'') to images from ID documents is a problem that can arise in various applications. A challenging instance of the problem arises when the face image…
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…