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20202022
most citedUnsupervised Enhancement of Soft-biometric Privacy with Negative Face Recognition

18 citations · 34 across the 7 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CV2021★ 4 cited

Pixel-Level Face Image Quality Assessment for Explainable Face Recognition

Philipp Terhörst, Marco Huber, Naser Damer +3

An essential factor to achieve high performance in face recognition systems is the quality of its samples. Since these systems are involved in daily life there is a strong need of…

cs.CV2021★ 4 cited

QMagFace: Simple and Accurate Quality-Aware Face Recognition

Philipp Terhörst, Malte Ihlefeld, Marco Huber +4

Face recognition systems have to deal with large variabilities (such as different poses, illuminations, and expressions) that might lead to incorrect matching decisions. These vari…

cs.CV2021

An Attack on Facial Soft-biometric Privacy Enhancement

Dailé Osorio-Roig, Christian Rathgeb, Pawel Drozdowski +3

In the recent past, different researchers have proposed privacy-enhancing face recognition systems designed to conceal soft-biometric attributes at feature level. These works have…

cs.CV2021

MiDeCon: Unsupervised and Accurate Fingerprint and Minutia Quality Assessment based on Minutia Detection Confidence

Philipp Terhörst, André Boller, Naser Damer +2

An essential factor to achieve high accuracies in fingerprint recognition systems is the quality of its samples. Previous works mainly proposed supervised solutions based on image…

cs.CV2021

A Comprehensive Study on Face Recognition Biases Beyond Demographics

Philipp Terhörst, Jan Niklas Kolf, Marco Huber +5

Face recognition (FR) systems have a growing effect on critical decision-making processes. Recent works have shown that FR solutions show strong performance differences based on th…