activity
20212024
most citedCR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability

20 citations · 28 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

A Survey on Drowsiness Detection -- Modern Applications and Methods

Biying Fu, Fadi Boutros, Chin-Teng Lin +1

Drowsiness detection holds paramount importance in ensuring safety in workplaces or behind the wheel, enhancing productivity, and healthcare across diverse domains. Therefore accur…

cs.AI2023★ 1 cited

Generalization of Fitness Exercise Recognition from Doppler Measurements by Domain-adaption and Few-Shot Learning

Biying Fu, Naser Damer, Florian Kirchbuchner +1

In previous works, a mobile application was developed using an unmodified commercial off-the-shelf smartphone to recognize whole-body exercises. The working principle was based on…

cs.CV2022

Towards Explaining Demographic Bias through the Eyes of Face Recognition Models

Biying Fu, Naser Damer

Biases inherent in both data and algorithms make the fairness of widespread machine learning (ML)-based decision-making systems less than optimal. To improve the trustfulness of su…

cs.CV2022

Face Morphing Attacks and Face Image Quality: The Effect of Morphing and the Unsupervised Attack Detection by Quality

Biying Fu, Naser Damer

Morphing attacks are a form of presentation attacks that gathered increasing attention in recent years. A morphed image can be successfully verified to multiple identities. This op…

cs.CV2021

Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations Through Activation Map Variation Analyses in Face Recognition Models

Biying Fu, Naser Damer

It is challenging to derive explainability for unsupervised or statistical-based face image quality assessment (FIQA) methods. In this work, we propose a novel set of explainabilit…

cs.CV2021★ 20 cited

CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability

Fadi Boutros, Meiling Fang, Marcel Klemt +2

The quality of face images significantly influences the performance of underlying face recognition algorithms. Face image quality assessment (FIQA) estimates the utility of the cap…

cs.CV2021★ 4 cited

The Effect of Wearing a Face Mask on Face Image Quality

Biying Fu, Florian Kirchbuchner, Naser Damer

Due to the COVID-19 situation, face masks have become a main part of our daily life. Wearing mouth-and-nose protection has been made a mandate in many public places, to prevent the…

cs.CV2021★ 3 cited

A Deep Insight into Measuring Face Image Utility with General and Face-specific Image Quality Metrics

Biying Fu, Cong Chen, Olaf Henniger +1

Quality scores provide a measure to evaluate the utility of biometric samples for biometric recognition. Biometric recognition systems require high-quality samples to achieve optim…