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Image Classification research benchmarks – Page 116 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

0.1Training FLOPs

15

Feb 26, 2026

94.56Accuracy

15

Feb 26, 2026

CIFAR-LT-100 Imbalance Factor 20 (test)

MetaSAug with cross-entropy loss

42.15Top-1 Error

15

Feb 26, 2026

CIFAR-LT-100 Imbalance Factor 200 (test)

MetaSAug with LDAM loss

56.91Top-1 Error

15

Feb 26, 2026

Pascal VOC 2007 (test)

92.6Accuracy

15

Feb 26, 2026

CIFAR10 4,000 labels (train)

12.41Error Rate

15

Feb 26, 2026

SVHN 1,000 labels (train)

3.96Error Rate (%)

15

Feb 26, 2026

CIFAR-100 (test)

10.7Test Error Rate

15

Feb 26, 2026

CIFAR-100 (test)

68.75Symmetric Noise (η=0.2) Accuracy

15

Feb 26, 2026

WebVision first 50 classes (val)

80.5Top-1 Accuracy

15

Feb 26, 2026

MNIST to MNIST-M

98.7Accuracy

15

Feb 26, 2026

ImageNet 3-hop split

6.3Flat Hit@1

15

Feb 26, 2026

ImageNet 2-hop split

26.6Flat Hit@1

15

Feb 26, 2026

94.84InD ACC

14

Jul 8, 2026

72.13Accuracy

14

Jul 7, 2026

CIFAR-100 (test)

71Accuracy

14

Jun 30, 2026

CIFAR-10 (test)

91.8Accuracy

14

Jun 30, 2026

81.14Accuracy (0% Attack Rate)

14

Jun 23, 2026

96.31Accuracy (0% Attack)

14

Jun 23, 2026

88.41Accuracy (0% Attack)

14

Jun 23, 2026

PACS Art Painting

86.9Accuracy (0% Attack Rate)

14

Jun 23, 2026

CIFAR-10H hard subset

64.8Accuracy

14

Jun 19, 2026

UC Merced (test)

99.93Accuracy

14

Jun 16, 2026

97.83Classification Accuracy (CA)

14

Jun 12, 2026

71.53CA

14

Jun 12, 2026

Page 116 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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