Face Recognition on MegaFace
98.64Verification RateFC-R50
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| FC-R50Training Dataset=Glint360k, Backbone=ResNet-502021.05 | 98.64 | — | |
| FC-R100Training Dataset=Webface42M, Backbone=ResNet-1002021.05 | 98.57 | — | |
| F2C-R100Training Dataset=Webface42M, Backbone=ResNet-1002021.05 | 98.53 | — | |
| FC-R50Training Dataset=MS1MV2, Backbone=ResNet-502021.05 | 97.82 | — | |
| F2C-R50Training Dataset=MS1MV2, Backbone=ResNet-502021.05 | 96.74 | — | |
| F2C-R50Training Dataset=Glint360k, Backbone=ResNet-502021.05 | 96.73 | — | |
| MobileFaceNetParams.(M)=2.0, MFLOPS=9332021.08 | 95.2 | 79.3 | |
| MixFaceNet-MParams.(M)=3.95, MFLOPS=626.12021.08 | 94.26 | 78.2 | |
| ShuffleMixFaceNet-MParams.(M)=3.95, MFLOPS=626.12021.08 | 94.24 | 78.13 | |
| VarGFaceNetParams.(M)=5.0, MFLOPS=10222021.08 | 93.9 | 78.2 | |
| ShuffleMixFaceNet-SParams.(M)=3.07, MFLOPS=451.72021.08 | 93.6 | 77.41 | |
| ShuffleFaceNet 1.5xParams.(M)=2.6, MFLOPS=577.52021.08 | 93 | 77.4 | |
| PocketNetM-256Params.(M)=1.75, MFLOPS=1099.152021.08 | 92.75 | 78.23 | |
| PocketNetM-128Params.(M)=1.68, MFLOPS=1099.022021.08 | 92.45 | 76.49 | |
| MixFaceNet-SParams.(M)=3.07, MFLOPS=451.72021.08 | 92.23 | 76.49 | |
| PocketNetS-256Params.(M)=0.99, MFLOPS=587.242021.08 | 91.77 | 76.53 | |
| MobileFaceNetV1Params.(M)=3.4, MFLOPS=11002021.08 | 91.3 | 76 | |
| FC-MobileTraining Dataset=MS1MV2, Backbone=Mobile2021.05 | 90.69 | — | |
| PocketNetS-128Params.(M)=0.92, MFLOPS=587.112021.08 | 90.54 | 75.81 | |
| MixFaceNet-XSParams.(M)=1.04, MFLOPS=161.92021.08 | 89.4 | 74.18 | |
| F2C-MobileTraining Dataset=MS1MV2, Backbone=Mobile2021.05 | 89.3 | — | |
| ShuffleMixFaceNet-XSParams.(M)=1.04, MFLOPS=161.92021.08 | 89.24 | 73.85 | |
| ProxylessFaceNASParams.(M)=3.2, MFLOPS=9002021.08 | 82.8 | 69.7 |