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Image Classification research benchmarks – Page 245 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

MB-MNIST synthetic (30% ratio)

94.04Accuracy

6

Feb 26, 2026

MB-MNIST synthetic (20% ratio)

89.11Accuracy

6

Feb 26, 2026

MB-MNIST synthetic (10% ratio)

62.21Accuracy

6

Feb 26, 2026

C-MNIST synthetic (5% ratio)

0.986Accuracy

6

Feb 26, 2026

C-MNIST synthetic (1% ratio)

98.4Accuracy

6

Feb 26, 2026

CIFAR-100 25-shot (test)

89.27Top-1 Accuracy

6

Feb 26, 2026

CIFAR-100 1-shot (test)

63.74Top-1 Accuracy

6

Feb 26, 2026

ImageNet-200 (I ∪ II) (test)

89.61Accuracy

6

Feb 26, 2026

ImageNet-100 II (test)

94.82ACC

6

Feb 26, 2026

ImageNet-100 (I) (test)

94.7Accuracy

6

Feb 26, 2026

Real-world COCO-based evaluation settings Stage 1 Discovery Precision@10 > 0.8

70.2Image Overall Precision

6

Feb 26, 2026

Real-world COCO-based evaluation settings Stage 1 Discovery Precision@10 > 0.6

69.8Image Overall Score

6

Feb 26, 2026

ImageNet-1K (val)

67.3NN Accuracy

6

Feb 26, 2026

61.7Best Accuracy

6

Feb 26, 2026

BFFHQ ratio 1.0 (test)

75.7Accuracy

6

Feb 26, 2026

BAR ratio 5.0 (test)

79.61Accuracy

6

Feb 26, 2026

Country211 (val)

Zero-Shot baseline

19.8Accuracy

6

Feb 26, 2026

Caltech256 (val)

85.4Accuracy

6

Feb 26, 2026

OfficeHome Real

10.18MAPE

6

Feb 27, 2026

OfficeHome ClipArt

11.7MAPE

6

Feb 27, 2026

13.94MAPE

6

Feb 27, 2026

6.79MAPE

6

Feb 27, 2026

1.95MAPE

6

Feb 27, 2026

4.73MAPE (%)

6

Feb 27, 2026

69.68Average Score

6

Feb 26, 2026

Page 245 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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