Fine-grained Image Classification on Cars 1.0 (val)
94.6AccuracyMPN-COV + SEB
Evaluation Results
| Method | Links | |
|---|---|---|
| MPN-COV + SEBBackbone=EfficientNet-b52022.05 | 94.6 | |
| MPN-COV + SEBBackbone=ResNet-1522022.05 | 94.1 | |
| MPN-COV + SEBBackbone=ResNet-1012022.05 | 93.9 | |
| MPN-COV + SEBBackbone=ResNet-502022.05 | 93.6 | |
| MPN-COVBackbone=EfficientNet-b52022.05 | 93.4 | |
| iSQRT-COVBackbone=EfficientNet-b52022.05 | 93.3 | |
| MPN-COV + SEBBackbone=VGG-162022.05 | 93 | |
| GPBackbone=VGG-162022.05 | 92.8 | |
| MPN-COVBackbone=ResNet-1522022.05 | 92.5 | |
| KPBackbone=VGG-162022.05 | 92.4 | |
| iSQRT-COVBackbone=ResNet-1522022.05 | 92.2 | |
| Improved B-CNNBackbone=VGG-162022.05 | 92 | |
| MoNetBackbone=VGG-162022.05 | 91.8 | |
| MPN-COVBackbone=ResNet-502022.05 | 91.7 | |
| MPN-COVBackbone=ResNet-1012022.05 | 91.7 | |
| iSQRT-COVBackbone=ResNet-1012022.05 | 91.5 | |
| iSQRT-COVBackbone=ResNet-502022.05 | 91.4 | |
| B-CNNBackbone=VGG-162022.05 | 91.3 | |
| KPBackbone=ResNet-502022.05 | 91.1 | |
| LRBPBackbone=VGG-162022.05 | 90.9 | |
| MPN-COVBackbone=VGG-162022.05 | 90.9 | |
| iSQRT-COVBackbone=VGG-162022.05 | 90.1 | |
| CBPBackbone=ResNet-502022.05 | 88.6 |