Fine-Grained Visual Categorization on CUB
92.1AccuracyTRD
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| TRD2023.10 | 92.1 | — | — | |
| Relational Proxies2023.10 | 92 | — | — | |
| SR-GNN2023.10 | 91.9 | — | — | |
| CAP2023.10 | 91.8 | — | — | |
| PMRC2023.10 | 91.8 | — | — | |
| TransFG2023.10 | 91.7 | — | — | |
| FFVT2023.10 | 91.65 | — | — | |
| WTFocus2023.10 | 90.8 | — | — | |
| MMAL2023.10 | 89.6 | — | — | |
| GaRD2023.10 | 89.6 | — | — | |
| DBTNet2023.10 | 88.1 | — | — | |
| MaxEnt2023.10 | 86.54 | — | — | |
| StochNorm2023.10 | 79.71 | — | — | |
| SR-GNNInput Size=224x2242022.09 | 0.919 | 30.9 | 9.8 | |
| TrnFGTransformer=ViT-B-16, Input Size=448x4482022.09 | 0.917 | — | — | |
| CAMFTransformer=Swin-224, Input Size=448x4482022.09 | 0.912 | — | — | |
| CAMFTransformer=Swin-224, Input Size=224x2242022.09 | 0.909 | — | — | |
| SwinTransformer=Swin-224, Input Size=448x4482022.09 | 0.907 | 88 | 47 | |
| ViTTransformer=ViT-B-16, Input Size=448x4482022.09 | 0.903 | 86 | 55.4 | |
| SwinTransformer=Swin-224, Input Size=224x2242022.09 | 0.897 | 88 | 15.4 |