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2023
Conference Paper
Title

EFaR 2023: Efficient Face Recognition Competition

Abstract
This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recognition models, the submitted solutions are ranked based on a weighted score of the achieved verification accuracies on a diverse set of benchmarks, as well as the deployability given by the number of floating-point operations and model size. The evaluation of submissions is extended to bias, cross-quality, and large-scale recognition benchmarks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines. The submitted solutions use small, efficient network architectures to reduce the computational cost, some solutions apply model quantization. An outlook on possible techniques that are underrepresented in current solutions is given as well.
Author(s)
Kolf, Jan Niklas  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Boutros, Fadi  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Elliesen, Jurek
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Theuerkauf, Markus
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Damer, Naser  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Alansari, Mohamad
Khalifa University
Abdul Hay, Oussama
Khalifa University
Alansari, Sara
Khalifa University
Javed, Sajid
Khalifa University
Werghi, Naoufel
Khalifa University
Grm, Klemen
University of Ljubljana  
Štruc, Vitomir
University of Ljubljana  
Alonso-Fernandez, Fernando
Halmstad University
Hernandez Diaz, Kevin
Halmstad University
Bigun, Josef
Halmstad University
George, Anjith
Idiap Research Institute
Ecabert, Christophe
Idiap Research Institute
Otroshi Shahreza, Hatef
Idiap Research Institute
Kotwal, Ketan
Idiap Research Institute
Marcel, Sébastien
Idiap Research Institute
Medvedev, Iurii
University of Coimbra  
Jin, Bo
University of Coimbra  
Nunes, Diogo
University of Coimbra  
Hassanpour, Ahmad
Norwegian University of Science and Technology  
Khatiwada, Pankaj
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Ahmad Toor, Aafan
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Yang, Bian
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Mainwork
IEEE International Joint Conference on Biometrics, IJCB 2023  
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
International Joint Conference on Biometrics 2023  
Open Access
DOI
10.1109/IJCB57857.2023.10448917
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

  • Deep learning

  • Efficiency

  • ATHENE

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