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Few-shot classification research benchmarks – Page 2 · SOTA2 Research

Few-shot classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

99.9Accuracy

66

May 26, 2026

93.25Accuracy

54

Feb 26, 2026

89.85Accuracy

54

Feb 26, 2026

CIFAR-FS (test)

97.64Mean Accuracy

51

Feb 26, 2026

88.95Accuracy

48

Feb 26, 2026

CUB bounding-box cropped 200-2011 (test)

92.8Accuracy

48

Feb 26, 2026

Meta-Dataset (test)

94.4Omniglot

48

Feb 26, 2026

32.1Accuracy

46

Feb 26, 2026

CPTAC k=25 positive samples (test)

98.1LUNG ST Accuracy

45

Feb 26, 2026

97.8LUNG ST Accuracy

45

Feb 26, 2026

85Avg Seen Accuracy

45

Feb 26, 2026

Omniglot 20-way 5-shot (test)

99.65Accuracy

43

Feb 26, 2026

Omniglot 20-way 1-shot (test)

99.12Accuracy

43

Feb 26, 2026

Meta-Dataset 1.0 (test)

77.02ILSVRC Accuracy

42

Feb 26, 2026

77.8Accuracy (1-shot)

41

Feb 26, 2026

tiered-ImageNet

85.15Accuracy (1-shot)

38

Feb 26, 2026

Laser welding molten pool image dataset (test)

85.64Accuracy

36

Jun 25, 2026

70.5Accuracy

36

May 15, 2026

PatternNet (19-19)

0.984Accuracy

36

Feb 26, 2026

84.77Accuracy

36

Feb 26, 2026

CUB Dirichlet alpha=2 (test)

94.6Accuracy

36

Feb 26, 2026

tiered-meta-iNat fine-grained

76.87Accuracy

36

Feb 26, 2026

meta-iNat fine-grained

91.84Accuracy

36

Feb 26, 2026

CUB200 5-way 1-shot

95.8Accuracy

36

Feb 26, 2026

miniImageNet Open-Ended 5-Way (test)

45.9Accuracy

35

Feb 27, 2026

Page 2 of 11

Popular datasets

ImageNet CUB Omniglot CIFAR ModelNet

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