| image-classification-on-oxford-iiit-pets-1 | CeiT-S (384 finetune resolution) | #1 | Accuracy: 94.9 |
| image-classification-on-oxford-iiit-pets-1 | CeiT-S | #3 | Accuracy: 94.6 |
| image-classification-on-oxford-iiit-pets-1 | CeiT-T (384 finetune resolution) | #4 | Accuracy: 94.5 |
| image-classification-on-oxford-iiit-pets-1 | CeiT-T | #5 | Accuracy: 93.8 |
| image-classification-on-stanford-cars | CeiT-S (384 finetune resolution) | #5 | Accuracy: 94.1 |
| image-classification-on-stanford-cars | CeiT-S | #8 | Accuracy: 93.2 |
| image-classification-on-stanford-cars | CeiT-T (384 finetune resolution) | #10 | Accuracy: 93 |
| image-classification-on-stanford-cars | CeiT-T | #12 | Accuracy: 90.5 |
| image-classification-on-inaturalist-2019 | CeiT-S (384 finetune resolution) | #8 | Top-1 Accuracy: 82.7 |
| image-classification-on-inaturalist-2019 | CeiT-S | #11 | Top-1 Accuracy: 78.9 |
| image-classification-on-inaturalist-2019 | CeiT-T (384 finetune resolution) | #12 | Top-1 Accuracy: 77.9 |
| image-classification-on-inaturalist-2019 | CeiT-T | #15 | Top-1 Accuracy: 72.8 |
| image-classification-on-inaturalist-2018 | CeiT-S (384 finetune resolution) | #16 | Top-1 Accuracy: 79.4% |
| image-classification-on-inaturalist-2018 | CeiT-S | #29 | Top-1 Accuracy: 73.3% |
| image-classification-on-inaturalist-2018 | CeiT-T (384 finetune resolution) | #32 | Top-1 Accuracy: 72.2% |
| image-classification-on-inaturalist-2018 | CeiT-T | #43 | Top-1 Accuracy: 64.3% |
| image-classification-on-cifar-10 | CeiT-S (384 finetune resolution) | #18 | Percentage correct: 99.1 |
| image-classification-on-cifar-10 | CeiT-S | #29 | Percentage correct: 99 |
| image-classification-on-cifar-10 | CeiT-T | #53 | Percentage correct: 98.5 |
| image-classification-on-cifar-100 | CeiT-S | #23 | Percentage correct: 91.8 |
| image-classification-on-cifar-100 | CeiT-S (384 finetune resolution) | #24 | Percentage correct: 91.8 |
| image-classification-on-cifar-100 | CeiT-T | #52 | Percentage correct: 89.4 |
| image-classification-on-cifar-100 | CeiT-T (384 finetune resolution) | #64 | Percentage correct: 88 |
| image-classification-on-flowers-102 | CeiT-S (384 finetune resolution) | #26 | Accuracy: 98.6 |
| image-classification-on-flowers-102 | CeiT-S | #33 | Accuracy: 98.2 |
| image-classification-on-flowers-102 | CeiT-T (384 finetune resolution) | #40 | Accuracy: 97.8 |
| image-classification-on-flowers-102 | CeiT-T | #46 | Accuracy: 96.9 |
| image-classification-on-imagenet-real | CeiT-S (384 finetune res) | #34 | Accuracy: 88.1% |
| image-classification-on-imagenet-real | CeiT-S | #40 | Accuracy: 87.3% |
| image-classification-on-imagenet-real | CeiT-T | #52 | Accuracy: 83.6% |
| image-classification-on-imagenet | CeiT-S (384 finetune res) | #469 | Top 1 Accuracy: 83.3%Number of params: 24.2MGFLOPs: 12.9 |
| image-classification-on-imagenet | CeiT-S | #615 | Top 1 Accuracy: 82%GFLOPs: 4.5 |
| image-classification-on-imagenet | CeiT-T (384 finetune res) | #843 | Top 1 Accuracy: 78.8%GFLOPs: 3.6 |
| image-classification-on-imagenet | CeiT-T | #955 | Top 1 Accuracy: 76.4%Number of params: 6.4MGFLOPs: 1.2 |