9 citations · 15 across the 7 of their papers we have counts for
8 papers
TransFIRA: Transfer Learning for Face Image Recognizability Assessment
Allen Tu, Kartik Narayan, Joshua Gleason +4
Face recognition in unconstrained environments such as surveillance, video, and web imagery must contend with extreme variation in pose, blur, illumination, and occlusion, where co…
Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift
Gina Wong, Joshua Gleason, Rama Chellappa +2
Learning models whose predictions are invariant under multiple environments is a promising approach for out-of-distribution generalization. Such models are trained to extract featu…
A Brief Survey on Person Recognition at a Distance
Chrisopher B. Nalty, Neehar Peri, Joshua Gleason +4
Person recognition at a distance entails recognizing the identity of an individual appearing in images or videos collected by long-range imaging systems such as drones or surveilla…
Where in the World is this Image? Transformer-based Geo-localization in the Wild
Shraman Pramanick, Ewa M. Nowara, Joshua Gleason +2
Predicting the geographic location (geo-localization) from a single ground-level RGB image taken anywhere in the world is a very challenging problem. The challenges include huge di…
Distill and De-bias: Mitigating Bias in Face Verification using Knowledge Distillation
Prithviraj Dhar, Joshua Gleason, Aniket Roy +3
Face recognition networks generally demonstrate bias with respect to sensitive attributes like gender, skintone etc. For gender and skintone, we observe that the regions of the fac…
PASS: Protected Attribute Suppression System for Mitigating Bias in Face Recognition
Prithviraj Dhar, Joshua Gleason, Aniket Roy +2
Face recognition networks encode information about sensitive attributes while being trained for identity classification. Such encoding has two major issues: (a) it makes the face r…
A Synthesis-Based Approach for Thermal-to-Visible Face Verification
Neehar Peri, Joshua Gleason, Carlos D. Castillo +3
In recent years, visible-spectrum face verification systems have been shown to match the performance of experienced forensic examiners. However, such systems are ineffective in low…
Towards Gender-Neutral Face Descriptors for Mitigating Bias in Face Recognition
Prithviraj Dhar, Joshua Gleason, Hossein Souri +2
State-of-the-art deep networks implicitly encode gender information while being trained for face recognition. Gender is often viewed as an important attribute with respect to ident…