Image Classification on ImageNet-1k (val) (Top-1 Accuracy, GMACs, and MParams)
84Top-1 AccShuffle Swin-B
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| Shuffle Swin-BBackbone=Transformer, # Params (M)=87.8, GMACs=15.6, Resolution=224x2242021.09 | 84 | 5.4 | 1 | |
| Swin Transformer-BBackbone=Transformer, # Params (M)=87.8, GMACs=15.4, Resolution=224x2242021.09 | 83.5 | 5.4 | 1 | |
| DeiT-BBackbone=Transformer, # Params (M)=86.6, GMACs=17.5, Resolution=224x2242021.09 | 83.4 | 4.8 | 1 | |
| AS-MLP-BBackbone=MLP, # Params (M)=88.0, GMACs=15.2, Resolution=224x2242021.09 | 83.3 | 5.4 | 1 | |
| ViP-Large/7Backbone=MLP, # Params (M)=87.8, GMACs=24.4, Resolution=224x2242021.09 | 83.2 | 3.4 | 0.9 | |
| CycleMLP-B5Backbone=MLP, # Params (M)=75.7, GMACs=12.3, Resolution=224x2242021.09 | 83.2 | 6.7 | 0.9 | |
| EfficientNet-B4Backbone=Convolution, # Params (M)=19.0, GMACs=4.2, Resolution=380x3802021.09 | 82.9 | 19.7 | 4.4 | |
| ViT-BBackbone=Transformer, # Params (M)=86.6, GMACs=17.5, Resolution=224x2242021.09 | 81.8 | 4.7 | 0.9 | |
| PVT-LBackbone=Transformer, # Params (M)=61.4, GMACs=9.8, Resolution=224x2242021.09 | 81.7 | 8.3 | 1.3 | |
| gMLP-BBackbone=MLP, # Params (M)=73.1, GMACs=15.8, Resolution=224x2242021.09 | 81.6 | 5.2 | 1.1 | |
| ViP-Small/7Backbone=MLP, # Params (M)=25.1, GMACs=6.9, Resolution=224x2242021.09 | 81.5 | 11.8 | 3.2 | |
| AS-MLP-TiBackbone=MLP, # Params (M)=28.0, GMACs=4.4, Resolution=224x2242021.09 | 81.3 | 18.7 | 2.9 | |
| DeiT-SBackbone=Transformer, # Params (M)=22.1, GMACs=4.6, Resolution=224x2242021.09 | 81.2 | 17.7 | 3.7 | |
| ResMLP-B24Backbone=MLP, # Params (M)=115.7, GMACs=23.0, Resolution=224x2242021.09 | 81 | 3.5 | 0.7 | |
| CCT-14tBackbone=Transformer, # Params (M)=22.4, GMACs=5.1, Resolution=224x2242021.09 | 80.7 | 15.8 | 3.6 | |
| RegNetY-16GFBackbone=Convolution, # Params (M)=83.6, GMACs=15.9, Resolution=224x2242021.09 | 80.4 | 5.1 | 1 | |
| ConvMLP-LBackbone=ConvMLP, # Params (M)=42.7, GMACs=9.9, Resolution=224x2242021.09 | 80.2 | 8.1 | 1.9 | |
| S^2-MLP-wideBackbone=MLP, # Params (M)=71.0, GMACs=14.0, Resolution=224x2242021.09 | 80 | 5.7 | 1.1 | |
| ViT-SBackbone=Transformer, # Params (M)=22.1, GMACs=4.6, Resolution=224x2242021.09 | 79.9 | 17.4 | 3.6 | |
| PVT-SBackbone=Transformer, # Params (M)=24.5, GMACs=3.8, Resolution=224x2242021.09 | 79.8 | 21 | 3.3 | |
| gMLP-SBackbone=MLP, # Params (M)=19.4, GMACs=4.5, Resolution=224x2242021.09 | 79.6 | 17.7 | 4.1 | |
| ResMLP-S24Backbone=MLP, # Params (M)=30.0, GMACs=6.0, Resolution=224x2242021.09 | 79.4 | 13.2 | 2.6 | |
| ConvMLP-MBackbone=ConvMLP, # Params (M)=17.4, GMACs=3.9, Resolution=224x2242021.09 | 79 | 20.3 | 4.5 | |
| RegNetY-8GFBackbone=Convolution, # Params (M)=39.2, GMACs=8.0, Resolution=224x2242021.09 | 79 | 9.9 | 2 | |
| CycleMLP-B1Backbone=MLP, # Params (M)=15.2, GMACs=2.1, Resolution=224x2242021.09 | 78.9 | 37.6 | 5.2 | |
| ResNet101Backbone=Convolution, # Params (M)=44.6, GMACs=7.8, Resolution=224x2242021.09 | 78 | 10 | 1.7 | |
| EfficientNet-B0Backbone=Convolution, # Params (M)=5.3, GMACs=0.4, Resolution=224x2242021.09 | 77.1 | 192.8 | 14.5 | |
| ConvMLP-SBackbone=ConvMLP, # Params (M)=9.0, GMACs=2.4, Resolution=224x2242021.09 | 76.8 | 32 | 8.5 | |
| ResMLP-S12Backbone=MLP, # Params (M)=15.3, GMACs=3.0, Resolution=224x2242021.09 | 76.6 | 25.5 | 5 | |
| MLP-Mixer-B/16Backbone=MLP, # Params (M)=59.9, GMACs=12.6, Resolution=224x2242021.09 | 76.4 | 6.1 | 1.3 | |
| ResNet50Backbone=Convolution, # Params (M)=25.6, GMACs=4.1, Resolution=224x2242021.09 | 76.1 | 18.6 | 3 | |
| Mobilenetv3Backbone=Convolution, # Params (M)=5.4, GMACs=0.2, Resolution=224x2242021.09 | 75.2 | 376 | 13.9 | |
| MLP-Mixer-S/16Backbone=MLP, # Params (M)=18.5, GMACs=3.8, Resolution=224x2242021.09 | 73.8 | 19.4 | 4 | |
| ResNet18Backbone=Convolution, # Params (M)=11.7, GMACs=1.8, Resolution=224x2242021.09 | 69.8 | 38.8 | 6 |