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

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cris.virtual.departmentFraunhofer-Institut für Graphische Datenverarbeitung IGD
cris.virtual.departmentFraunhofer-Institut für Graphische Datenverarbeitung IGD
cris.virtual.orcid0000-0003-4516-9128
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dc.contributor.authorMelzi, Pietro
dc.contributor.authorTolosana, Ruben
dc.contributor.authorVera-Rodriguez, Ruben
dc.contributor.authorMinchul, Kim
dc.contributor.authorRathgeb, Christian
dc.contributor.authorXiaoming, Liu
dc.contributor.authorDeAndres-Tame, Ivan
dc.contributor.authorMorales , Aythami
dc.contributor.authorFierrez, Julian
dc.contributor.authorOrtega-Garcia, Javier
dc.contributor.authorZhao, Weisong
dc.contributor.authorZhu, Xiangyu
dc.contributor.authorYan, Zheyu
dc.contributor.authorZhang, Xiao-Yu
dc.contributor.authorWu, Jinlin
dc.contributor.authorLei, Zhen
dc.contributor.authorTripathi, Suvidha
dc.contributor.authorKothari, Mahak
dc.contributor.authorZama, Md Haider
dc.contributor.authorDeb, Debayan
dc.date.accessioned2024-05-02T11:10:44Z
dc.date.available2024-05-02T11:10:44Z
dc.date.issued2024
dc.description.abstractDespite 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.
dc.description.endpage901
dc.description.startpage892
dc.identifier.doi10.1109/WACVW60836.2024.00100
dc.identifier.scopus2-s2.0-85187740269
dc.identifier.urihttps://publica.fraunhofer.de/handle/publica/467104
dc.language.isoen
dc.relation.conferenceWinter Conference on Applications of Computer Vision 2024
dc.relation.doi#PLACEHOLDER_PARENT_METADATA_VALUE#
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dc.relation.grantno#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.relation.grantno860813
dc.relation.isbn#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.relation.projectNext Generation Biometric Systems
dc.relation.projectNext Generation Biometric Systems
dc.relation.projectTRaining in Secure and PrivAcy-preserving biometricS
dc.relation.publicationIEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2024. Proceedings
dc.subjectBranche: Information Technology
dc.subjectResearch Line: Computer vision (CV)
dc.subjectResearch Line: Human computer interaction (HCI)
dc.subjectResearch Line: Machine learning (ML)
dc.subjectLTA: Interactive decision-making support and assistance systems
dc.subjectLTA: Machine intelligence, algorithms, and data structures (incl. semantics)
dc.subjectLTA: Generation, capture, processing, and output of images and 3D models
dc.subjectBiometrics
dc.subjectFace recognition
dc.subjectImage generation
dc.subjectMachine learning
dc.subjectDeep learning
dc.subjectATHENE
dc.titleFRCSyn Challenge at WACV 2024: Face Recognition Challenge in the Era of Synthetic Data
dc.typeconference paper
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oairecerif.author.affiliationUniversidad Autonoma de Madrid
oairecerif.author.affiliationUniversidad Autonoma de Madrid
oairecerif.author.affiliationMichigan State University
oairecerif.author.affiliationHochschule Darmstadt
oairecerif.author.affiliationMichigan State University
oairecerif.author.affiliationUniversidad Autonoma de Madrid
oairecerif.author.affiliationUniversidad Autonoma de Madrid
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publica.rights.oaOpen Access
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publica.rights.timestamp2026-04-03 15:50:30.964947

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