EFaR 2023: Efficient Face Recognition Competition
2023 IEEE INTERNATIONAL JOINT CONFERENCE ON BIOMETRICS, IJCB(2023)
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.
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Key words
Face Recognition,Efficient Recognition,Efficient Face Recognition,Benchmark,Model Size,Floating-point Operations,Quantification Model,Accuracy Verification,Face Recognition Model,Learning Rate,Convolutional Neural Network,Computational Complexity,Deep Neural Network,Convolutional Layers,Batch Size,Stochastic Gradient Descent,Competitive Results,Global Average Pooling,Final Ranking,Memory Footprint,False Acceptance Rate,Neural Architecture Search,Masked Faces,Compact Network,SqueezeNet,AdamW Optimizer,Top-ranked Model,Backbone Architecture,Stochastic Gradient Descent Optimizer,Loss Function
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