Image Classification on Food-101

Metric: Accuracy (%) (higher is better)

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#	Model↕	Accuracy (%)▼	Extra Data	Paper	Date↕	Code
1	Bamboo (ViTB/16)	92.9	Yes	Bamboo: Building Mega-Scale Vision Dataset Conti...	2022-03-15	Code
2	Semi-SST (ViT-Base, 10% Labels)	91.5	Yes	SST: Self-training with Self-adaptive Thresholdi...	2025-05-31	-
3	Super-SST (ViT-Base, 10% Labels)	91.1	Yes	SST: Self-training with Self-adaptive Thresholdi...	2025-05-31	-
4	SEER (RegNet10B - linear eval)	90.3	Yes	Vision Models Are More Robust And Fair When Pret...	2022-02-16	Code
5	TWIST (ResNet-50)	89.3	No	Self-Supervised Learning by Estimating Twin Clas...	2021-10-14	Code
6	Semi-SST (ViT-Base, 1% Labels)	86.5	Yes	SST: Self-training with Self-adaptive Thresholdi...	2025-05-31	-
7	TransBoost-ResNet50	84.3	No	TransBoost: Improving the Best ImageNet Performa...	2022-05-26	Code
8	Super-SST (ViT-Base, 1% Labels)	83.4	Yes	SST: Self-training with Self-adaptive Thresholdi...	2025-05-31	-
9	MANO-tiny	82.48	Yes	Linear Attention with Global Context: A Multipol...	2025-07-03	Code
10	NNCLR	76.7	No	With a Little Help from My Friends: Nearest-Neig...	2021-04-29	Code
11	Inception V3	71.67	No	-	-	Code