Classification on VGG Flowers
69.17AccuracyFNG-CE
Evaluation Results
| Method | Links | |
|---|---|---|
| FNG-CEBackbone=ResNet-182026.03 | 69.17 | |
| CEBackbone=ResNet-182026.03 | 68.85 | |
| CE+L2Backbone=ResNet-182026.03 | 68.01 | |
| FNG-CEBackbone=ResNet-502026.03 | 65.05 | |
| CEBackbone=ResNet-502026.03 | 64.37 | |
| CE+L2Backbone=ResNet-502026.03 | 62.46 | |
| MetaMAEPretrain data=ImageNet32, Protocol=Linear evaluation2023.10 | 36.3 | |
| e-MixPretrain data=ImageNet32, Protocol=Linear evaluation2023.10 | 26 | |
| MAEPretrain data=ImageNet32, Protocol=Linear evaluation2023.10 | 22.2 | |
| CapriPretrain data=ImageNet32, Protocol=Linear evaluation2023.10 | 18.6 | |
| ShEDPretrain data=ImageNet32, Protocol=Linear evaluation2023.10 | 13 | |
| BaselinePretrain data=ImageNet32, Protocol=Linear evaluation2023.10 | 9 |