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Benchmarks
Image Classification on ImageNet 1-shot (train)
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53.1
Accuracy
MAE-CTmin
7.236
19.143
31.05
42.957
Apr 20, 2023
Accuracy
Updated 4d ago
Evaluation Results
Method
Method
Links
Accuracy
MAE-CTmin
Architecture=ViT-H/16
2023.04
53.1
MAE-CTmin
Architecture=ViT-L/16
2023.04
51.8
MSN
Architecture=ViT-B/16
2023.04
50.3
MAE-CTaug
Architecture=ViT-H/16
2023.04
50.1
MAE-CTaug
Architecture=ViT-L/16
2023.04
49.6
iBOT
Architecture=ViT-L/16
2023.04
48.5
Layer Grafting
Architecture=ViT-L/16
2023.04
47.8
MSN
Architecture=ViT-L/16
2023.04
47.5
iBOT
Architecture=ViT-B/16
2023.04
45.3
Layer Grafting
Architecture=ViT-B/16
2023.04
40
MAE-CTaug
Architecture=ViT-B/16
2023.04
37.5
MoCo v3
Architecture=ViT-B/16
2023.04
37.4
MAE-CTmin
Architecture=ViT-B/16
2023.04
31.1
MAE
Architecture=ViT-L/16
2023.04
14.3
MAE
Architecture=ViT-B/16
2023.04
14
MAE
Architecture=ViT-H/16
2023.04
9
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