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Papers Benchmarks Datasets Tasks

Image Classification research benchmarks – Page 184 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Flowers102 Pathological Non-IID (test)

96.23Accuracy

9

Feb 26, 2026

Caltech101 Pathological Non-IID (test)

97.02Accuracy

9

Feb 26, 2026

DTD Pathological Non-IID (test)

87.67Accuracy

9

Feb 26, 2026

Food101 Pathological Non-IID (test)

92.73Accuracy

9

Feb 26, 2026

Tiny-ImageNet-C Severity 1-5

0.4Accuracy

9

Feb 26, 2026

Tiny-ImageNet-C Severity 5

31.67Accuracy

9

Feb 26, 2026

CIFAR-100-C Severity 1-5

71.22Accuracy

9

Feb 26, 2026

CIFAR-10-C Severity 1-5

87.88Accuracy

9

Feb 26, 2026

85.7Top-1 Acc

9

Feb 26, 2026

ImageNette 10 classes (val)

UR–JEPA(LCGLT)

91.41Top-1 Acc

9

Jun 2, 2026

CIFAR100 Dirichlet 0.6 (test)

99.75Client Acc Exceedance Rate

9

Feb 26, 2026

CIFAR100 Dirichlet 0.1 (test)

97.29Percent Clients Acc_p > Acc_g

9

Feb 26, 2026

CIFAR-100 (test)

75.22Standard Accuracy

9

Feb 26, 2026

78.1Accuracy

9

Feb 26, 2026

MNIST-scale ideal downsampling, missing scales 1.0 (test)

99.14Accuracy

9

Feb 26, 2026

MNIST-scale non-ideal downsampling (test)

98.8Accuracy

9

Feb 26, 2026

CIFAR100 (test)

0.483Natural Accuracy

9

Feb 26, 2026

CIFAR-100 (beta=0.3) (test)

centralized learning

73.98Test Accuracy

9

Feb 27, 2026

CIFAR-100 beta=0.6 (test)

centralized learning

73.98Test Accuracy

9

Feb 27, 2026

CIFAR-10 beta=0.6 (test)

centralized learning

92.55Accuracy (Test)

9

Feb 27, 2026

ImageNet 1k (val)

80.2Top-1 Acc (1% labels)

9

Feb 26, 2026

55.94Accuracy

9

Feb 26, 2026

FEMNIST 10 new writers (test)

88.18Overall Accuracy

9

Feb 26, 2026

CIFAR-100 ImageNet-1K transfer (test)

0.613SA

9

Feb 26, 2026

ImageNet-1K 1.0 (val)

76.18ID Accuracy

9

Feb 26, 2026

Page 184 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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