1 citations · 3 across the 8 of their papers we have counts for
8 papers
Synthetic Data for Face Recognition: Current State and Future Prospects
Fadi Boutros, Vitomir Struc, Julian Fierrez +1
Over the past years, deep learning capabilities and the availability of large-scale training datasets advanced rapidly, leading to breakthroughs in face recognition accuracy. Howev…
Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition
Jan Niklas Kolf, Tim Rieber, Jurek Elliesen +3
Many of the commonly used datasets for face recognition development are collected from the internet without proper user consent. Due to the increasing focus on privacy in the socia…
Are Explainability Tools Gender Biased? A Case Study on Face Presentation Attack Detection
Marco Huber, Meiling Fang, Fadi Boutros +1
Face recognition (FR) systems continue to spread in our daily lives with an increasing demand for higher explainability and interpretability of FR systems that are mainly based on…
MorDIFF: Recognition Vulnerability and Attack Detectability of Face Morphing Attacks Created by Diffusion Autoencoders
Naser Damer, Meiling Fang, Patrick Siebke +3
Investigating new methods of creating face morphing attacks is essential to foresee novel attacks and help mitigate them. Creating morphing attacks is commonly either performed on…
SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
Marco Huber, Fadi Boutros, Anh Thi Luu +16
This paper presents a summary of the Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data (SYN-MAD) held at the 2022 International Joint Con…
OCFR 2022: Competition on Occluded Face Recognition From Synthetically Generated Structure-Aware Occlusions
Pedro C. Neto, Fadi Boutros, Joao Ribeiro Pinto +12
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022). OCFR-2022 a…