Lightweight Face Recognition
12 papers with code • 7 benchmarks • 5 datasets
Lightweight Face Recognition models are a group of face recognition models with lightweight backbones, which can be used for mobile or edge device applications.
Benchmarks
These leaderboards are used to track progress in Lightweight Face Recognition
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LFW
IJB-C
IJB-B
CALFW
Most implemented papers
QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization
fdbtrs/QuantFace
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Deep learning-based face recognition models follow the common trend in deep neural networks by utilizing full-precision floating-point networks with high computational costs.
EFaR 2023: Efficient Face Recognition Competition
otroshi/edgeface
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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.
