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Image Classification research benchmarks – Page 51 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

CIFAR-100 Sym-50% (test)

69.77Accuracy

32

Feb 26, 2026

SYN NUMBERS to SVHN (test)

0.971Accuracy

32

Feb 26, 2026

CIFAR-10 AutoAttack v1 (AA)

76.04Accuracy

31

Jul 7, 2026

CIFAR-10-LT (gamma=200) (test)

66.01Accuracy

31

Jun 4, 2026

SynDigits-LT gamma=50

89.8Accuracy

31

Jun 4, 2026

84.5Accuracy

31

Mar 31, 2026

36.39Robust Accuracy

31

Apr 1, 2026

EMNIST Dir(0.5) (test)

91.82Test Accuracy

31

Apr 21, 2026

CIFAR-10 (test)

94.64Accuracy

31

Feb 27, 2026

Noisy Student Training (L2)

77.8Top-1 Accuracy

31

Jul 2, 2026

CIFAR-10 standard (test)

4.08Top-1 Error Rate

31

Feb 26, 2026

2.03Top-1 Error Rate

31

Feb 26, 2026

OrganSMNIST v2 (test)

85.28Accuracy

31

Feb 26, 2026

70.6Accuracy

31

Feb 26, 2026

8 Vision Tasks Aggregate ViT-B/32 ViT-L/14 (average)

94.3Accuracy

31

Feb 26, 2026

92.1Mean Accuracy

31

Mar 5, 2026

98.5Accuracy (KNN)

31

Apr 14, 2026

CIFAR-100 non-IID alpha=0.1

66.98Accuracy

31

Mar 4, 2026

85.9Accuracy (Natural)

31

Feb 26, 2026

79.9Top-1 Acc

31

Feb 26, 2026

Describable Textures Dataset (DTD) (test)

78Accuracy

31

Jul 8, 2026

CIFAR-10 10% labeled data (test)

CLIMB + FedReLa

79.03All Accuracy

31

Jun 25, 2026

22.8Top-1 Acc

31

Feb 26, 2026

MNIST to SVHN standard (test)

97.16Accuracy

31

Feb 26, 2026

0.003Error Rate

31

Feb 26, 2026

Page 51 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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