Face Identification On Megaface
Metrics
Accuracy
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | Accuracy |
|---|---|
| ghostfacenets-lightweight-face-recognition | 98.64% |
| cosface-large-margin-cosine-loss-for-deep | 82.72% |
| unified-negative-pair-generation-toward-well | 99.27% |
| partial-fc-training-10-million-identities-on | 99.10% |
| sphereface-deep-hypersphere-embedding-for | 75.766% |
| unified-negative-pair-generation-toward-well | 98.03% |
| arcface-additive-angular-margin-loss-for-deep | 98.35% |
| deep-polynomial-neural-networks | 98.78% |
| facenet-a-unified-embedding-for-face | 70.49% |
| a-light-cnn-for-deep-face-representation-with | 73.749% |
| support-vector-guided-softmax-loss-for-face | 97.2% |
| sphereface-deep-hypersphere-embedding-for | 72.729% |
| unified-negative-pair-generation-toward-well | 98.82% |