FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of
  Synthetic Data
Pietro Melzi Ruben Tolosana Ruben Vera-Rodriguez Minchul Kim Christian Rathgeb Xiaoming Liu Ivan DeAndres-Tame Aythami Morales Julian Fierrez Javier Ortega-Garcia Weisong Zhao Xiangyu Zhu Zheyu Yan Xiao-Yu Zhang Jinlin Wu Zhen Lei Suvidha Tripathi Mahak Kothari Md Haider Zama Debayan Deb Bernardo Biesseck Pedro Vidal Roger Granada Guilherme Fickel Gustavo Führ David Menotti Alexander Unnervik Anjith George Christophe Ecabert Hatef Otroshi Shahreza Parsa Rahimi Sébastien Marcel Ioannis Sarridis Christos Koutlis Georgia Baltsou Symeon Papadopoulos Christos Diou Nicolò Di Domenico Guido Borghi Lorenzo Pellegrini Enrique Mas-Candela Ángela Sánchez-Pérez Andrea Atzori Fadi Boutros Naser Damer Gianni Fenu Mirko Marras
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.