Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge
  in the Era of Synthetic Data
Ivan DeAndres-Tame Ruben Tolosana Pietro Melzi Ruben Vera-Rodriguez Minchul Kim Christian Rathgeb Xiaoming Liu Aythami Morales Julian Fierrez Javier Ortega-Garcia Zhizhou Zhong Yuge Huang Yuxi Mi Shouhong Ding Shuigeng Zhou Shuai He Lingzhi Fu Heng Cong Rongyu Zhang Zhihong Xiao Evgeny Smirnov Anton Pimenov Aleksei Grigorev Denis Timoshenko Kaleb Mesfin Asfaw Cheng Yaw Low Hao Liu Chuyi Wang Qing Zuo Zhixiang He Hatef Otroshi Shahreza Anjith George Alexander Unnervik Parsa Rahimi Sébastien Marcel Pedro C. Neto Marco Huber Jan Niklas Kolf Naser Damer Fadi Boutros Jaime S. Cardoso Ana F. Sequeira Andrea Atzori Gianni Fenu Mirko Marras Vitomir Štruc Jiang Yu Zhangjie Li Jichun Li Weisong Zhao Zhen Lei Xiangyu Zhu Xiao-Yu Zhang Bernardo Biesseck Pedro Vidal Luiz Coelho Roger Granada David Menotti
Synthetic data is gaining increasing relevance for training machine learning
models. This is mainly motivated due to several factors such as the lack of
real data and intra-class variability, time and errors produced in manual
labeling, and in some cases privacy concerns, among others. This paper presents
an overview of the 2nd edition of the Face Recognition Challenge in the Era of
Synthetic Data (FRCSyn) organized at CVPR 2024. FRCSyn aims to investigate the
use of synthetic data in face recognition to address current technological
limitations, including data privacy concerns, demographic biases,
generalization to novel scenarios, and performance constraints in challenging
situations such as aging, pose variations, and occlusions. Unlike the 1st
edition, in which synthetic data from DCFace and GANDiffFace methods was only
allowed to train face recognition systems, in this 2nd edition we propose new
sub-tasks that allow participants to explore novel face generative methods. The
outcomes of the 2nd FRCSyn Challenge, along with the proposed experimental
protocol and benchmarking contribute significantly to the application of
synthetic data to face recognition.