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Image Classification research benchmarks – Page 64 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

83.6Top-1 Acc

25

Feb 26, 2026

CIFAR-10 automobile vs. cat

99.8AUC

25

Feb 26, 2026

MNIST digits 8 and 9

99.2AUC

25

Feb 26, 2026

MNIST iid (10 classes/client) CONV4, 50 rounds (test)

99.4Accuracy

25

Feb 26, 2026

ImageNet-A OfficeHome source (test)

46.1Accuracy

25

Feb 26, 2026

ImageNet-R OfficeHome source (test)

0.772Accuracy

25

Feb 26, 2026

ImageNet-A MiniDomainnet source (test)

61.48Accuracy

25

Feb 26, 2026

ImageNet-R MiniDomainnet source (test)

70.18Accuracy

25

Feb 26, 2026

90.8Clean Accuracy

25

Feb 27, 2026

ImageNet-1K 1.0 (val)

64.21-shot Acc

25

Feb 26, 2026

98.57Accuracy

25

Feb 26, 2026

CIFAR10 original and noisy labels (test)

93.8Top-1 Acc

25

Feb 26, 2026

86.15Accuracy

25

May 26, 2026

ImageNet-1K original (val)

80.1Top-1 Acc

25

Feb 26, 2026

CIFAR-100 LT IF=10

65.5Top-1 Accuracy

25

Jul 8, 2026

CIFAR-100 50+50

74.71Joint Accuracy

25

Feb 26, 2026

CheXpert (test)

89.5AUC

25

Feb 26, 2026

78.26Top-1 Accuracy

25

Feb 26, 2026

CIFAR-100 Noisy (test)

75.2Top-1 Accuracy

25

Jun 30, 2026

CIFAR100 (test)

82.22Top-1 Acc

25

Feb 26, 2026

Terra Incognita (test)

62.9Accuracy

25

Feb 26, 2026

STL-10 USB (test)

5.65Error Rate

25

Feb 26, 2026

CIFAR-100-LT IR=100 (test)

55.9Accuracy

25

Feb 26, 2026

ImageNet-1k (val)

2.6FLOPs (G)

25

Feb 26, 2026

CIFAR10 epsilon = 8/255 (test)

95Clean Accuracy

25

Jun 2, 2026

Page 64 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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