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Image Classification research benchmarks – Page 309 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Caltech-101 8-shot

97.2Accuracy

3

Feb 26, 2026

Oxford Flowers 102 8-shot

98.3Accuracy

3

Feb 26, 2026

Oxford-IIIT Pets 8-shot

95.2Accuracy

3

Feb 26, 2026

Food-101 8-shot

91.4Accuracy

3

Feb 26, 2026

Stanford Cars 8-shot

88.2Accuracy

3

Feb 26, 2026

89.8Accuracy

3

Feb 26, 2026

FGVC Aircraft 8-shot

57.6Accuracy

3

Feb 26, 2026

79.2Accuracy

3

Feb 26, 2026

Standard CLIP Evaluation Suite (IN-1K, Caltech, CUB, DTD, ESAT, FLO, SUN, UCF) (test)

64.7IN-1K Accuracy

3

Feb 26, 2026

52.65Accuracy (alpha=0.1)

3

Feb 26, 2026

CIFAR-100 (test)

60.88Final Test Accuracy

3

Feb 26, 2026

TinyImageNet 2015 (test)

21.7Accuracy

3

Feb 26, 2026

CIFAR-100 2009 (test)

37.6Accuracy

3

Feb 26, 2026

Country211 (test)

21.1Accuracy

3

Feb 26, 2026

CIFAR-10 (test)

70.8Acc (L-inf)

3

Feb 26, 2026

ImageNet-1k 1.0 (val)

83.9Top-1 Acc

3

Feb 26, 2026

CIFAR-10 (test)

90.56Accuracy (p=0.2)

3

Feb 26, 2026

Mean of 7 transfer datasets (test)

0.554Accuracy (1-shot)

3

Feb 26, 2026

21.8Acc (1-shot)

3

Feb 26, 2026

56.71-shot Accuracy

3

Feb 26, 2026

Resisc45 (test)

67.6Accuracy (1-shot)

3

Feb 26, 2026

53.5Accuracy (1-shot)

3

Feb 26, 2026

27.11-shot Accuracy

3

Feb 26, 2026

CIFAR100 (test)

67.81-shot Acc

3

Feb 26, 2026

93.8Accuracy (1-shot)

3

Feb 26, 2026

Page 309 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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