2 citations · 2 across the 5 of their papers we have counts for
5 papers
Lights, Camera, Matching: The Role of Image Illumination in Fair Face Recognition
Gabriella Pangelinan, Grace Bezold, Haiyu Wu +2
Facial brightness is a key image quality factor impacting face recognition accuracy differentials across demographic groups. In this work, we aim to decrease the accuracy gap betwe…
Goldilocks Test Sets for Face Verification
Haiyu Wu, Sicong Tian, Aman Bhatta +6
Reported face verification accuracy has reached a plateau on current well-known test sets. As a result, some difficult test sets have been assembled by reducing the image quality o…
Beard Segmentation and Recognition Bias
Kagan Ozturk, Grace Bezold, Aman Bhatta +2
A person's facial hairstyle, such as presence and size of beard, can significantly impact face recognition accuracy. There are publicly-available deep networks that achieve reasona…
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…
Logical Consistency and Greater Descriptive Power for Facial Hair Attribute Learning
Haiyu Wu, Grace Bezold, Aman Bhatta +1
Face attribute research has so far used only simple binary attributes for facial hair; e.g., beard / no beard. We have created a new, more descriptive facial hair annotation scheme…