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ResearchFormerly WizWand

Image Classification on ImageNet-1k (val) (Top-1 Accuracy, GMACs, and MParams)

84Top-1 AccShuffle Swin-B
69.23273.06676.980.734Sep 9, 2021
Updated 8mo ago

Evaluation results

MethodLinks
Shuffle Swin-BBackbone=Transformer, # Params (M)=87.8, GMACs=15.6, Resolution=224x2242021.09845.41
Swin Transformer-BBackbone=Transformer, # Params (M)=87.8, GMACs=15.4, Resolution=224x2242021.0983.55.41
DeiT-BBackbone=Transformer, # Params (M)=86.6, GMACs=17.5, Resolution=224x2242021.0983.44.81
AS-MLP-BBackbone=MLP, # Params (M)=88.0, GMACs=15.2, Resolution=224x2242021.0983.35.41
ViP-Large/7Backbone=MLP, # Params (M)=87.8, GMACs=24.4, Resolution=224x2242021.0983.23.40.9
CycleMLP-B5Backbone=MLP, # Params (M)=75.7, GMACs=12.3, Resolution=224x2242021.0983.26.70.9
EfficientNet-B4Backbone=Convolution, # Params (M)=19.0, GMACs=4.2, Resolution=380x3802021.0982.919.74.4
ViT-BBackbone=Transformer, # Params (M)=86.6, GMACs=17.5, Resolution=224x2242021.0981.84.70.9
PVT-LBackbone=Transformer, # Params (M)=61.4, GMACs=9.8, Resolution=224x2242021.0981.78.31.3
gMLP-BBackbone=MLP, # Params (M)=73.1, GMACs=15.8, Resolution=224x2242021.0981.65.21.1
ViP-Small/7Backbone=MLP, # Params (M)=25.1, GMACs=6.9, Resolution=224x2242021.0981.511.83.2
AS-MLP-TiBackbone=MLP, # Params (M)=28.0, GMACs=4.4, Resolution=224x2242021.0981.318.72.9
DeiT-SBackbone=Transformer, # Params (M)=22.1, GMACs=4.6, Resolution=224x2242021.0981.217.73.7
ResMLP-B24Backbone=MLP, # Params (M)=115.7, GMACs=23.0, Resolution=224x2242021.09813.50.7
CCT-14tBackbone=Transformer, # Params (M)=22.4, GMACs=5.1, Resolution=224x2242021.0980.715.83.6
RegNetY-16GFBackbone=Convolution, # Params (M)=83.6, GMACs=15.9, Resolution=224x2242021.0980.45.11
ConvMLP-LBackbone=ConvMLP, # Params (M)=42.7, GMACs=9.9, Resolution=224x2242021.0980.28.11.9
S^2-MLP-wideBackbone=MLP, # Params (M)=71.0, GMACs=14.0, Resolution=224x2242021.09805.71.1
ViT-SBackbone=Transformer, # Params (M)=22.1, GMACs=4.6, Resolution=224x2242021.0979.917.43.6
PVT-SBackbone=Transformer, # Params (M)=24.5, GMACs=3.8, Resolution=224x2242021.0979.8213.3
gMLP-SBackbone=MLP, # Params (M)=19.4, GMACs=4.5, Resolution=224x2242021.0979.617.74.1
ResMLP-S24Backbone=MLP, # Params (M)=30.0, GMACs=6.0, Resolution=224x2242021.0979.413.22.6
ConvMLP-MBackbone=ConvMLP, # Params (M)=17.4, GMACs=3.9, Resolution=224x2242021.097920.34.5
RegNetY-8GFBackbone=Convolution, # Params (M)=39.2, GMACs=8.0, Resolution=224x2242021.09799.92
CycleMLP-B1Backbone=MLP, # Params (M)=15.2, GMACs=2.1, Resolution=224x2242021.0978.937.65.2
ResNet101Backbone=Convolution, # Params (M)=44.6, GMACs=7.8, Resolution=224x2242021.0978101.7
EfficientNet-B0Backbone=Convolution, # Params (M)=5.3, GMACs=0.4, Resolution=224x2242021.0977.1192.814.5
ConvMLP-SBackbone=ConvMLP, # Params (M)=9.0, GMACs=2.4, Resolution=224x2242021.0976.8328.5
ResMLP-S12Backbone=MLP, # Params (M)=15.3, GMACs=3.0, Resolution=224x2242021.0976.625.55
MLP-Mixer-B/16Backbone=MLP, # Params (M)=59.9, GMACs=12.6, Resolution=224x2242021.0976.46.11.3
ResNet50Backbone=Convolution, # Params (M)=25.6, GMACs=4.1, Resolution=224x2242021.0976.118.63
Mobilenetv3Backbone=Convolution, # Params (M)=5.4, GMACs=0.2, Resolution=224x2242021.0975.237613.9
MLP-Mixer-S/16Backbone=MLP, # Params (M)=18.5, GMACs=3.8, Resolution=224x2242021.0973.819.44
ResNet18Backbone=Convolution, # Params (M)=11.7, GMACs=1.8, Resolution=224x2242021.0969.838.86