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  4. Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
 
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2024
Conference Paper
Title

Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data

Abstract
Synthetic data is gaining increasing relevance for train ing 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 la beling, 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 in vestigate the use of synthetic data in face recognition to ad dress current technological limitations, including data pri vacy concerns, demographic biases, generalization to novel scenarios, and performance constraints in challenging sit uations such as aging, pose variations, and occlusions. Un like 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 genera tive methods. The outcomes of the 2nd FRCSyn Challenge, along with the proposed experimental protocol and bench marking contribute significantly to the application of syn thetic data to face recognition.
Author(s)
DeAndres-Tame, Ivan
Universidad Autonoma de Madrid
Tolosana, Ruben
Universidad Autonoma de Madrid
Melzi, Pietro
Universidad Autonoma de Madrid
Vera-Rodriguez, Ruben
Universidad Autonoma de Madrid
Kim, Minchul
Michigan State University
Rathgeb, Christian
Hochschule Darmstadt  
Liu, Xiaoming
Michigan State University
Morales, Aythami
Universidad Autonoma de Madrid
Fierrez, Julian
Universidad Autonoma de Madrid
Ortega-Garcia, Javier
Universidad Autonoma de Madrid
Zhong, Zhizhou
Fudan University
Huang, Yuge
Tencent Youtu Lab
Mi, Yuxi
Fudan University
Ding, Shouhong
Tencent Youtu Lab
Zhou, Shuigeng
He, Shuai
Interactive Entertainment Group of Netease Inc
Fu, Lingzhi
Interactive Entertainment Group of Netease Inc
Cong, Heng
Interactive Entertainment Group of Netease Inc
Zhang, Rongyu
Interactive Entertainment Group of Netease Inc
Xiao, Zhihong
Interactive Entertainment Group of Netease Inc
Smirnov, Evgeny
ID R&D Inc.
Pimenov, Anton
ID R&D Inc.
Grigorev, Aleksei
ID R&D Inc.
Timoshenko, Denis
ID R&D Inc.
Asfaw, Kaleb Mesfin
Korea Advanced Institute of Science and Technology -KAIST-  
Yaw Low, Cheng
Institute for Basic Science
Liu, Hao
China Telecom AI
Wang, Chuyi
China Telecom AI
Zuo, Qing
China Telecom AI
He, Zhixiang
China Telecom AI
Shahreza, Hatef Otroshi
Idiap Research Institute
George, Anjith
Idiap Research Institute
Unnervik, Alexander
Idiap Research Institute
Rahimi, Parsa
Idiap Research Institute
Marcel, Sébastien
Idiap Research Institute
Neto, Pedro C.
INESC TEC
Huber, Marco  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kolf, Jan Niklas  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Damer, Naser  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Boutros, Fadi  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Cardoso, Jaime S.
INESC TEC
Sequeira, Ana F.
INESC TEC
Atzori, Andrea
University of Cagliari
Fenu, Gianni
University of Cagliari
Marras, Mirko
University of Cagliari
Štruc, Vitomir
University of Ljubljana  
Yu, Jiang
Samsung Electronics (China) R&D Centre
Li, Zhangjie
Samsung Electronics (China) R&D Centre
Li, Jichun
Samsung Electronics (China) R&D Centre
Zhao, Weisong
IIE, CAS
Lei, Zhen
MAIS, CASIA
Zhu, Xiangyu
MAIS, CASIA
Zhang, Xiao-Yu
IIE, CAS
Biesseck, Bernardo
Federal University of Paraná
Vidal, Pedro
Federal University of Paraná
Coelho, Luiz
unico - idTech
Granada, Roger
unico - idTech
Menotti, David
Federal University of Paraná
Mainwork
IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024. Proceedings  
Project(s)
Next Generation Biometric Systems  
Next Generation Biometric Systems  
Funder
Bundesministerium für Bildung und Forschung -BMBF-
Hessisches Ministerium für Wissenschaft und Kunst -HMWK-  
Conference
Conference on Computer Vision and Pattern Recognition Workshops 2024  
Face Recognition Challenge in the Era of Synthetic Data 2024  
Open Access
DOI
10.1109/CVPRW63382.2024.00323
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Branche: Information Technology

  • Research Line: Computer vision (CV)

  • Research Line: Human computer interaction (HCI)

  • Research Line: Machine learning (ML)

  • LTA: Interactive decision-making support and assistance systems

  • LTA: Machine intelligence, algorithms, and data structures (incl. semantics)

  • LTA: Generation, capture, processing, and output of images and 3D models

  • Biometrics

  • Face recognition

  • Machine learning

  • ATHENE

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