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 [BibTeX] [Marc21]
EFaR 2023: Efficient Face Recognition Competition
Type of publication: Conference paper
Citation: George_IJCB2023-2_2023
Publication status: Published
Booktitle: IEEE International Joint Conference on Biometrics (IJCB 2023)
Year: 2023
ISSN: 2474-9680
ISBN: 979-8-3503-3726-6
Abstract: This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held within the 2023 In- ternational Joint Conference on Biometrics (IJCB 2023). The competition received 17 submissions from 6 different teams. To drive further development of efficient face recog- nition models, the submitted solutions are ranked based on a weighted score of the achieved verification accura- cies on a diverse set of benchmarks, as well as the de- ployability 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 bench- marks. Overall, the paper gives an overview of the achieved performance values of the submitted solutions as well as a diverse set of baselines, the methodologies used to achieve lightweight and efficient face recognition solutions, and out- looks on possible techniques that are underrepresented in current solutions.
Projects Idiap
Authors George, Anjith
Ecabert, Christophe
Otroshi Shahreza, Hatef
Kotwal, Ketan
Marcel, S├ębastien
Added by: [UNK]
Total mark: 0
  • George_IJCB2023-2_2023.pdf