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

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

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.
Author(s)
Melzi, Pietro
Universidad Autonoma de Madrid
Tolosana, Ruben
Universidad Autonoma de Madrid
Vera-Rodriguez, Ruben
Universidad Autonoma de Madrid
Minchul, Kim
Michigan State University
Rathgeb, Christian
Hochschule Darmstadt  
Xiaoming, Liu
Michigan State University
DeAndres-Tame, Ivan
Universidad Autonoma de Madrid
Morales , Aythami
Universidad Autonoma de Madrid
Fierrez, Julian
Universidad Autonoma de Madrid
Ortega-Garcia, Javier
Universidad Autonoma de Madrid
Zhao, Weisong
IIE, CAS
Zhu, Xiangyu
MAIS, CASIA
Yan, Zheyu
MAIS, CASIA
Zhang, Xiao-Yu
IIE, CAS
Wu, Jinlin
CAIR, HKISI, CAS
Lei, Zhen
MAIS, CASIA
Tripathi, Suvidha
LENS, Inc.
Kothari, Mahak
Suvidha
Zama, Md Haider
LENS, Inc.
Deb, Debayan
LENS, Inc.
Biesseck, Bernardo
Federal University of Parana
Vidal, Pedro
Federal University of Parana
Granada, Roger
unico - idTech
Fickel, Guilherme
unico - idTech
Führ, Gustavo
unico - idTech
Menotti, David
Federal University of Parana
Unnervik, Alexander
Idiap Research Institute
George, Anjith
Idiap Research Institute
Ecabert, Christophe
Idiap Research Institute
Hatef Shahreza, Otroshi
Idiap Research Institute
Rahimi, Parsa
Idiap Research Institute
Marcel, Sébastien
Idiap Research Institute
Sarridis, Ioannis
Centre for Research and Technology Hellas
Koutlis, Christos
Centre for Research and Technology Hellas
Baltsou, Georgia
Centre for Research and Technology Hellas
Papadopoulos, Symeon
Centre for Research and Technology Hellas
Diou, Christos
Harokopio University of Athens
Di Domenico, Nicolò
University of Bologna
Borghi, Guido
University of Bologna  
Pellegrini, Lorenzo
University of Bologna  
Mas-Candela, Enrique
Facephi
Sánchez-Pérez, Ángela
Facephi
Atzori, Andrea
University of Cagliari
Fenu, Gianni
University of Cagliari
Boutros, Fadi  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Marras, Mirko
University of Cagliari
Damer, Naser  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2024. Proceedings  
Project(s)
Next Generation Biometric Systems  
Next Generation Biometric Systems  
TRaining in Secure and PrivAcy-preserving biometricS  
Funder
Bundesministerium für Bildung und Forschung -BMBF-  
Hessisches Ministerium für Wissenschaft und Kunst -HMWK-  
European Commission  
Conference
Winter Conference on Applications of Computer Vision 2024  
DOI
10.1109/WACVW60836.2024.00100
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

  • Image generation

  • Machine learning

  • Deep learning

  • ATHENE

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