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FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data

Authors :
Melzi, Pietro
Tolosana, Ruben
Vera-Rodriguez, Ruben
Kim, Minchul
Rathgeb, Christian
Liu, Xiaoming
DeAndres-Tame, Ivan
Morales, Aythami
Fierrez, Julian
Ortega-Garcia, Javier
Zhao, Weisong
Zhu, Xiangyu
Yan, Zheyu
Zhang, Xiao-Yu
Wu, Jinlin
Lei, Zhen
Tripathi, Suvidha
Kothari, Mahak
Zama, Md Haider
Deb, Debayan
Biesseck, Bernardo
Vidal, Pedro
Granada, Roger
Fickel, Guilherme
Führ, Gustavo
Menotti, David
Unnervik, Alexander
George, Anjith
Ecabert, Christophe
Shahreza, Hatef Otroshi
Rahimi, Parsa
Marcel, Sébastien
Sarridis, Ioannis
Koutlis, Christos
Baltsou, Georgia
Papadopoulos, Symeon
Diou, Christos
Di Domenico, Nicolò
Borghi, Guido
Pellegrini, Lorenzo
Mas-Candela, Enrique
Sánchez-Pérez, Ángela
Atzori, Andrea
Boutros, Fadi
Damer, Naser
Fenu, Gianni
Marras, Mirko
Publication Year :
2023

Abstract

Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail. This paper offers an overview of the Face Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized at WACV 2024. This is the first international challenge aiming to explore the use of synthetic data in face recognition to address existing limitations in the technology. Specifically, the FRCSyn Challenge targets concerns related to data privacy issues, demographic biases, generalization to unseen scenarios, and performance limitations in challenging scenarios, including significant age disparities between enrollment and testing, pose variations, and occlusions. The results achieved in the FRCSyn Challenge, together with the proposed benchmark, contribute significantly to the application of synthetic data to improve face recognition technology.<br />Comment: 10 pages, 1 figure, WACV 2024 Workshops

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2311.10476
Document Type :
Working Paper