Pyramid Adversarial Training Improves ViT Performance

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Benchmark Model Rank Results
domain-generalization-on-imagenet-aPyramid Adversarial Training Improves ViT (Im21k)#12Top-1 accuracy %: 62.44
domain-generalization-on-imagenet-aPyramid Adversarial Training Improves ViT (384x384)#23Top-1 accuracy %: 36.41
domain-generalization-on-imagenet-cPyramid Adversarial Training Improves ViT (Im21k)#9mean Corruption Error (mCE): 36.80Number of params: 87M
domain-generalization-on-imagenet-cPyramid Adversarial Training Improves ViT#15mean Corruption Error (mCE): 41.42
domain-generalization-on-imagenet-rPyramid Adversarial Training Improves ViT (Im21k)#16Top-1 Error Rate: 42.16
domain-generalization-on-imagenet-rPyramid Adversarial Training Improves ViT#21Top-1 Error Rate: 46.08
domain-generalization-on-imagenet-sketchPyramid Adversarial Training Improves ViT (Im21k)#13Top-1 accuracy: 46.03
domain-generalization-on-imagenet-sketchPyramid Adversarial Training Improves ViT#17Top-1 accuracy: 41.04
image-classification-on-objectnetViT-B/16 (512x512) + Pyramid#24Top-1 Accuracy: 49.39
image-classification-on-objectnetViT-B/16 (512x512) + Pixel#26Top-1 Accuracy: 47.53
image-classification-on-objectnetViT-B/16 (512x512)#29Top-1 Accuracy: 46.68
image-classification-on-objectnetRegViT on 384x384 + Adv Pyramid#37Top-1 Accuracy: 39.79
image-classification-on-objectnetRegViT on 384x384 + Adv Pixel#41Top-1 Accuracy: 37.41
image-classification-on-objectnetRegViT on 384x384#45Top-1 Accuracy: 35.59
image-classification-on-objectnetRegViT on 384x384 + Random Pyramid#47Top-1 Accuracy: 34.83
image-classification-on-objectnetRegViT on 384x384 + Random Pixel#49Top-1 Accuracy: 34.12
image-classification-on-objectnetRegViT (RandAug) + Adv Pyramid#50Top-1 Accuracy: 32.92
image-classification-on-objectnetDiscrete ViT + Pixel#54Top-1 Accuracy: 30.98
image-classification-on-objectnetDiscrete ViT + Pyramid#55Top-1 Accuracy: 30.28
image-classification-on-objectnetRegViT (RandAug) + Adv Pixel#56Top-1 Accuracy: 30.11
image-classification-on-objectnetDiscrete ViT#57Top-1 Accuracy: 29.95
image-classification-on-objectnetRegViT (RandAug) + Random Pyramid#58Top-1 Accuracy: 29.41
image-classification-on-objectnetRegViT (RandAug)#59Top-1 Accuracy: 29.3
image-classification-on-objectnetRegViT (RandAug) + Random Pixel#62Top-1 Accuracy: 28.72
image-classification-on-objectnetMLP-Mixer + Pyramid#63Top-1 Accuracy: 28.6
image-classification-on-objectnetMLP-Mixer#68Top-1 Accuracy: 25.9
image-classification-on-objectnetViT + MixUp#70Top-1 Accuracy: 25.65
image-classification-on-objectnetMLP-Mixer + Pixel#72Top-1 Accuracy: 24.75
image-classification-on-objectnetViT + CutMix#75Top-1 Accuracy: 21.61
image-classification-on-objectnetViT#79Top-1 Accuracy: 17.36

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