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Image Classification research benchmarks – Page 286 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

VISTA-Beyond Flowers

48.9Accuracy

4

Feb 26, 2026

VISTA-Beyond Pokemon

64.5Accuracy

4

Feb 26, 2026

VISTA-Beyond Plants

30Accuracy

4

Feb 26, 2026

VISTA-Beyond Landmark

45.3Accuracy

4

Feb 26, 2026

VISTA-Beyond Insects Spider

25.8Accuracy

4

Feb 26, 2026

VISTA-Beyond Food

30.4Accuracy

4

Feb 26, 2026

VISTA-Beyond FolkArt

29.3Accuracy

4

Feb 26, 2026

VISTA-Beyond Attire

36.1Accuracy

4

Feb 26, 2026

VISTA-Beyond Architecture

41Accuracy

4

Feb 26, 2026

VISTA-Beyond Animals

27.3Accuracy

4

Feb 26, 2026

CIFAR-100 (test)

62.84Accuracy

4

Feb 26, 2026

CIFAR-10 (test)

86.44Accuracy

4

Feb 26, 2026

99.42Accuracy

4

Feb 26, 2026

CIFAR-10C frost level 4

16.9Error Rate

4

Feb 26, 2026

Zennit (Attn-LRP)

146ABPC

4

Feb 26, 2026

1.77ABPC

4

Feb 26, 2026

CIFAR-10 5,000 images (subset)

81.9Accuracy

4

Feb 26, 2026

ImageNet 10-class subset (test)

Feature-space Smoothing (FS)

94.2Certified Accuracy (eps=0.00)

4

Feb 27, 2026

MNIST 30% symmetric noise (test)

95.56Accuracy

4

Feb 26, 2026

0.477Red.

4

Feb 26, 2026

94.53Accuracy (20% Noise)

4

Feb 26, 2026

-0.986LPPD

4

Feb 26, 2026

CIFAR-100 20 x 5 scenario (test)

44.81Accuracy

4

Feb 26, 2026

CIFAR-100 40 + 30 + 30 scenario (test)

50.38Accuracy

4

Feb 26, 2026

CIFAR-100 50 + 50 scenario (test)

58.79Accuracy

4

Feb 26, 2026

Page 286 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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