Image Classification On Omnibenchmark

Average Top-1 Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Tableau comparatif

Nom du modèle	Average Top-1 Accuracy
bamboo-building-mega-scale-vision-dataset	45.4
parameter-efficient-transfer-learning-for-nlp	44.5
beit-bert-pre-training-of-image-transformers	30.1
billion-scale-semi-supervised-learning-for	40.4
inception-v4-inception-resnet-and-the-impact	32.3
re-labeling-imagenet-from-single-to-multi	30.8
neural-prompt-search	47.6
masked-autoencoders-are-scalable-vision	30.6
manifold-mixup-better-representations-by	31.6
mlp-mixer-an-all-mlp-architecture-for-vision	32.2
deep-residual-learning-for-image-recognition	37.4
deep-residual-learning-for-image-recognition	34.3
momentum-contrast-for-unsupervised-visual	34.8
swin-transformer-hierarchical-vision	46.4
mopro-webly-supervised-learning-with-momentum	36.1
efficientnet-rethinking-model-scaling-for	35.8
learning-transferable-visual-models-from	42.1
emerging-properties-in-self-supervised-vision	38.9
large-scale-learning-of-general-visual	40.4
unsupervised-learning-of-visual-features-by	38.3
cutmix-regularization-strategy-to-train	31.1
meal-v2-boosting-vanilla-resnet-50-to-80-top	36.6