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Papers Benchmarks Datasets Tasks

Image Classification research benchmarks – Page 248 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Efficient-CapsNet

94.9Top-2 Accuracy

6

Feb 26, 2026

VLCS OOD accuracy

99.5Accuracy (C)

6

Feb 26, 2026

75.56Diversity

6

Feb 26, 2026

64.9Accuracy

6

Feb 26, 2026

43.83Natural Accuracy

6

Feb 26, 2026

0.792Top-1 Accuracy

6

Feb 26, 2026

ColorMNIST (test)

89.9Accuracy

6

Feb 26, 2026

Random texture MNIST (test)

56.57Accuracy

6

Feb 27, 2026

CIFAR-10N Random Noise (test)

95.3Accuracy

6

Feb 26, 2026

46.7Clean Accuracy

6

Feb 26, 2026

CIFAR100 (test)

22.05R@1

6

Feb 26, 2026

44.97R@1

6

Feb 26, 2026

CIFAR-100 10000 labeled samples

72.48Top-1 Acc

6

Feb 26, 2026

CIFAR-100 (2500 labeled samples)

67.09Top-1 Acc

6

Feb 26, 2026

CIFAR-100 400 labeled samples

53.94Top-1 Accuracy

6

Feb 26, 2026

CIFAR-10 4000 labeled samples

95.62Top-1 Acc

6

Feb 26, 2026

CIFAR-10 standard (train=4K, unlabeled=41K)

UDA + 'Consist.'

3.95Error Rate

6

Feb 26, 2026

ImageNet1k (val)

74.02Top-1 Accuracy

6

Feb 26, 2026

ImageNet16-120 (test)

50.58Clean Accuracy

6

Feb 26, 2026

68.6Accuracy

6

Feb 26, 2026

ImageNet-A standard (test)

0.282Accuracy

6

Feb 26, 2026

ImageNet-Sketch standard (test)

35.8Accuracy

6

Feb 26, 2026

98.08Top-1 Accuracy (Seed 0)

6

Feb 26, 2026

88.4Accuracy (Noise 0.1)

6

Feb 26, 2026

ImageNet 1K (val)

81.3Top-1 Accuracy

6

Feb 26, 2026

Page 248 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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