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SotA/Methodology/Face Recognition/CFP-FP

Face Recognition on CFP-FP

Metric: Accuracy (higher is better)

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#Model↕Accuracy▼AugmentationsPaperDate↕Code
1GhostFaceNetV2-10.9933No--Code
2SymFace + AdaFace + ResNet100 +WebFace0.992NoSymFace: Additional Facial Symmetry Loss for Dee...2024-09-18-
3ElasticFace-Arc0.9867NoElasticFace: Elastic Margin Loss for Deep Face R...2021-09-20Code
4DiscFace0.9854No---
5CircleLoss(ours)0.9602NoCircle Loss: A Unified Perspective of Pair Simil...2020-02-25Code
6EdgeFace - S (g=0.5)0.9581NoEdgeFace: Efficient Face Recognition Model for E...2023-07-04Code
7EdgeFace - S (g=0.5)0.9581NoEdgeFace: Efficient Face Recognition Model for E...2023-07-04Code
8EdgeFace - XS (g=0.6)0.9437NoEdgeFace: Efficient Face Recognition Model for E...2023-07-04Code
9PocketNetS0.9334NoPocketNet: Extreme Lightweight Face Recognition ...2021-08-24Code
10Seesaw-shuffleFaceNet(mobi)0.9307NoSeesawFaceNets: sparse and robust face verificat...2019-08-24Code
11DCQ0.9287NoDynamic Class Queue for Large Scale Face Recogni...2021-05-24Code
12SynthDistill0.9089NoSynthDistill: Face Recognition with Knowledge Di...2023-08-28Code
13DigiFace-1M0.8981NoDigiFace-1M: 1 Million Digital Face Images for F...2022-10-05Code
14IDiff-Face0.8547NoIDiff-Face: Synthetic-based Face Recognition thr...2023-08-09Code
15QMagFace0.8395NoQMagFace: Simple and Accurate Quality-Aware Face...2021-11-26Code