CeiT-T (384 finetune resolution)

Reported on 5 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision5 results

Image ClassificationonStanford Cars
Accuracy· 2021-03-22
93
best: 96.868 (efficient adaptive ensembling)
Incorporating Convolution Designs into Visual Transformers arXiv:2103.11816
Image ClassificationonOxford-IIIT Pets
Accuracy· 2021-03-22
94.5
best: 97.1 (EffNet-L2 (SAM))
Incorporating Convolution Designs into Visual Transformers arXiv:2103.11816
Image ClassificationonFlowers-102
Accuracy· uses extra data· 2021-03-22
97.8
best: 99.76 (CCT-14/7x2)
Incorporating Convolution Designs into Visual Transformers arXiv:2103.11816
Image ClassificationoniNaturalist 2019
Top-1 Accuracy· uses extra data· 2021-03-22
77.9
best: 88.5 (Hiera-H (448px))
Incorporating Convolution Designs into Visual Transformers arXiv:2103.11816
Image ClassificationonCIFAR-100
Percentage correct· uses extra data· 2021-03-22
88
best: 96.08 (EffNet-L2 (SAM))
Incorporating Convolution Designs into Visual Transformers arXiv:2103.11816