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Lightweight Face Recognition

Lightweight Face Recognition models are a group of face recognition models with lightweight backbones, which can be used for mobile or edge device applications.

Papers

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Showing 1–14 of 14 papers

TitleStatusHype
GhostFaceNets: Lightweight Face Recognition Model From Cheap OperationsCode2
EFaR 2023: Efficient Face Recognition CompetitionCode1
EdgeFace: Efficient Face Recognition Model for Edge DevicesCode1
QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit QuantizationCode1
PocketNet: Extreme Lightweight Face Recognition Network using Neural Architecture Search and Multi-Step Knowledge DistillationCode1
MixFaceNets: Extremely Efficient Face Recognition NetworksCode1
ShrinkTeaNet: Million-scale Lightweight Face Recognition via Shrinking Teacher-Student NetworksCode1
MobileFaceNets: Efficient CNNs for Accurate Real-Time Face Verification on Mobile DevicesCode1
Lightweight Face Recognition: An Improved MobileFaceNet Model—0
SynthDistill: Face Recognition with Knowledge Distillation from Synthetic DataCode0
SqueezeFacePoseNet: Lightweight Face Verification Across Different Poses for Mobile Platforms—0
VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face RecognitionCode0
Towards Flops-constrained Face RecognitionCode0
SeesawFaceNets: sparse and robust face verification model for mobile platformCode0
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