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Image Classification
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Food-101
Image Classification on Food-101
Metric: Accuracy (%) (higher is better)
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Model
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Accuracy (%)
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Extra Data
Paper
Date
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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
#1
Bamboo (ViTB/16)
SOTA
92.9
Accuracy (%)
· Extra Data
· 2022-03-15
Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergy
Code
#2
Semi-SST (ViT-Base, 10% Labels)
91.5
Accuracy (%)
· Extra Data
· 2025-05-31
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
#3
Super-SST (ViT-Base, 10% Labels)
91.1
Accuracy (%)
· Extra Data
· 2025-05-31
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
#4
SEER (RegNet10B - linear eval)
SOTA
90.3
Accuracy (%)
· Extra Data
· 2022-02-16
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Code
#5
TWIST (ResNet-50)
SOTA
89.3
Accuracy (%)
· 2021-10-14
Self-Supervised Learning by Estimating Twin Class Distributions
Code
#6
Semi-SST (ViT-Base, 1% Labels)
86.5
Accuracy (%)
· Extra Data
· 2025-05-31
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
#7
TransBoost-ResNet50
84.3
Accuracy (%)
· 2022-05-26
TransBoost: Improving the Best ImageNet Performance using Deep Transduction
Code
#8
Super-SST (ViT-Base, 1% Labels)
83.4
Accuracy (%)
· Extra Data
· 2025-05-31
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning
#9
MANO-tiny
82.48
Accuracy (%)
· Extra Data
· 2025-07-03
Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and Physics
Code
#10
NNCLR
SOTA
76.7
Accuracy (%)
· 2021-04-29
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations
Code
#11
Inception V3
71.67
Accuracy (%)
No paper
Code