Fine-grained Image Classification on iNaturalist 2017
82AccuracyMetaFormer
Evaluation results
| Method | Links | |
|---|---|---|
| MetaFormerBackbone=MetaFormer-1, Pretrain=iNat212022.03 | 82 | |
| MDCMBackbone=MS-ViT-Base2025.04 | 79.8 | |
| MetaFormerBackbone=MetaFormer-1, Pretrain=ImageNet-21k2022.03 | 79.4 | |
| MetaFormerBackbone=MetaFormer-1, Pretrain=ImageNet-1k2022.03 | 78.2 | |
| M2FormerBackbone=MS-ViT-Base2025.04 | 77.8 | |
| ACC-ViTBackbone=ViT Base2025.04 | 77 | |
| FixSENetBackbone=SENet-154, Pretrain=ImageNet-1k2022.03 | 75.4 | |
| SRGNBackbone=ResNet502025.04 | 73.6 | |
| MFVTBackbone=ViT Base2025.04 | 72.6 | |
| TransFGBackbone=ViT Base2025.04 | 71.7 | |
| TransFGBackbone=ViT-B-16, Pretrain=ImageNet-21k2022.03 | 70.9 | |
| SIM-TransBackbone=ViT Base2025.04 | 69.9 | |
| AF-TransBackbone=ViT Base2025.04 | 68.9 | |
| RAMS-TransBackbone=ViT Base2025.04 | 68.5 | |
| TASNBackbone=ResNet502025.04 | 68.2 | |
| IARGBackbone=ResNet1012025.04 | 66.8 | |
| SSNBackbone=ResNet1012025.04 | 65.2 |