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EFaR 2023: Efficient Face Recognition Competition

Kolf, Jan Niklas ; Boutros, Fadi ; Elliesen, Jurek ; Theuerkauf, Markus ; Damer, Naser ; Alansari, Mohamad ; Hay, Oussama Abdul ; Alansari, Sara ; Javed, Sajid ; Werghi, Naoufel ; Grm, Klemen ; Štruc, Vitomir ; Alonso-Fernandez, Fernando ; Diaz, Kevin Hernandez ; Bigun, Josef ; George, Anjith ; Ecabert, Christophe ; Shahreza, Hatef Otroshi ; Kotwal, Ketan ; Marcel, Sébastien ; Medvedev, Iurii ; Jin, Bo ; Nunes, Diogo ; Hassanpour, Ahmad ; Khatiwada, Pankaj ; Toor, Aafan Ahmad ; Yang, Bian (2023)
EFaR 2023: Efficient Face Recognition Competition.
International Joint Conference on Biometrics 2023. Ljubljana, Slovenia (25.-28.9.2023)
doi: 10.1109/IJCB57857.2023.10448917
Conference or Workshop Item, Bibliographie

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.

Item Type: Conference or Workshop Item
Erschienen: 2023
Creators: Kolf, Jan Niklas ; Boutros, Fadi ; Elliesen, Jurek ; Theuerkauf, Markus ; Damer, Naser ; Alansari, Mohamad ; Hay, Oussama Abdul ; Alansari, Sara ; Javed, Sajid ; Werghi, Naoufel ; Grm, Klemen ; Štruc, Vitomir ; Alonso-Fernandez, Fernando ; Diaz, Kevin Hernandez ; Bigun, Josef ; George, Anjith ; Ecabert, Christophe ; Shahreza, Hatef Otroshi ; Kotwal, Ketan ; Marcel, Sébastien ; Medvedev, Iurii ; Jin, Bo ; Nunes, Diogo ; Hassanpour, Ahmad ; Khatiwada, Pankaj ; Toor, Aafan Ahmad ; Yang, Bian
Type of entry: Bibliographie
Title: EFaR 2023: Efficient Face Recognition Competition
Language: English
Date: 29 September 2023
Publisher: IEEE
Book Title: 2023 IEEE International Joint Conference on Biometrics (IJCB)
Event Title: International Joint Conference on Biometrics 2023
Event Location: Ljubljana, Slovenia
Event Dates: 25.-28.9.2023
DOI: 10.1109/IJCB57857.2023.10448917
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.

Uncontrolled Keywords: Biometrics, Face recognition, Machine learning, Deep learning, Efficiency
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 12 Apr 2024 10:35
Last Modified: 12 Apr 2024 10:35
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