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Papers Benchmarks Datasets Tasks

Image Classification research benchmarks – Page 223 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

CIFAR-20 Class-prior Shift 100 (test)

40.27Mean Accuracy

7

Feb 26, 2026

CIFAR-20 Class-prior Shift 10 (test)

49.17Mean Accuracy

7

Feb 26, 2026

CIFAR-20 Label Noise 0.4 (test)

45.48Mean Accuracy

7

Feb 26, 2026

CIFAR-20 Label Noise 0.2 (test)

54.19Mean Accuracy

7

Feb 26, 2026

Color-MNIST Class-prior Shift 100 (test)

88.34Mean Accuracy

7

Feb 26, 2026

Color-MNIST Class-prior Shift 10 (test)

94.43Mean Accuracy

7

Feb 26, 2026

Color-MNIST Label Noise 0.4 (test)

90.09Mean Accuracy

7

Feb 26, 2026

Color-MNIST Label Noise 0.2 (test)

0.91Mean Accuracy

7

Feb 26, 2026

MNIST LN 0.4 (test)

88.84Mean Accuracy

7

Feb 26, 2026

MNIST LN 0.2 (test)

91.44Accuracy

7

Feb 26, 2026

72Top-1 Acc

7

Feb 26, 2026

76.4Top-1 Accuracy

7

Feb 26, 2026

86.45Clean Accuracy

7

Feb 26, 2026

CIFAR-100 (test)

76.95Clean Accuracy

7

Feb 26, 2026

MNIST 5000 train, 8000 (test)

96.74Accuracy

7

Feb 26, 2026

ImageNet-S 1.0 (val)

48.3Top-1 Accuracy

7

Feb 26, 2026

ImageNet 1k (val)

90.52Accuracy

7

Feb 26, 2026

CelebA HeavyMakeup

0.982Guiding Score

7

Feb 26, 2026

CelebA HairColor

94.97Guiding Score

7

Feb 26, 2026

Digit-Five 200 clients (test)

89.8Test Accuracy

7

Feb 26, 2026

Digit-Five 100 clients (test)

91.1Accuracy

7

Feb 26, 2026

Digit-Five 50 clients (test)

92.7Test Accuracy

7

Feb 26, 2026

ImageNet-1K Robustness Variants (IN-1K, IN-V2, IN-ReaL, IN-Adv., IN-Ren., IN-Ske.) 1.0 (val)

88.5Top-1 Acc (IN-1K)

7

Feb 26, 2026

DomainNet Real domain (ID)

73.16Accuracy

7

Feb 26, 2026

ImageNet subset (test)

49.89Accuracy (Natural)

7

Feb 26, 2026

Page 223 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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