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Papers Benchmarks Datasets Tasks

Image Classification research benchmarks – Page 129 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

Average (CIFAR, CUB, Flowers, Food, Pets, VWW)

88.75Top-1 Accuracy

13

Feb 26, 2026

CIFAR-10-LT (ρ = 0.1)

86.37Test Accuracy

13

May 4, 2026

CIFAR-10-LT ρ = 0.01

68.81Accuracy

13

May 4, 2026

m-forestnet (test)

55.9Mean Accuracy

13

Mar 10, 2026

86.7Accuracy

13

Feb 26, 2026

97.9Acc

13

Feb 26, 2026

CIFAR100 standard (test)

79.84Top-1 Accuracy

13

Feb 26, 2026

94Top-1 Accuracy

13

Feb 26, 2026

CIFAR100 (test)

79.9Accuracy

13

Feb 26, 2026

MNIST non-iid (4 classes/client) (test)

99Accuracy

13

Feb 26, 2026

84.2Accuracy (Metric 1)

13

Feb 26, 2026

17.24Latency (ms/iter)

13

Feb 26, 2026

69.68Accuracy (Q->C)

13

Feb 26, 2026

11-dataset VLM Generalization Suite base-to-novel

81.6Avg Acc

13

Feb 27, 2026

ImageNet-1K (val)

82.9Top-1 Accuracy

13

Feb 26, 2026

Waterhemp (test)

81.91mAcc

13

Feb 26, 2026

Cotton Leaf Disease Dataset (test)

CottonLeafVision

98Accuracy

13

Jun 15, 2026

26.36Gaussian Blur Error Rate

13

Feb 26, 2026

Food101 5-way 5-shot (test)

79.59Accuracy (%)

13

Feb 26, 2026

Oxford-IIIT Pet 5-way 5-shot (test)

95.44Accuracy

13

Feb 26, 2026

Stanford Dogs 5-way 5-shot (test)

91.35Accuracy

13

Feb 26, 2026

Flowers102 5-way 5-shot (test)

99.89Accuracy

13

Feb 26, 2026

Caltech256 5-way 5-shot (test)

93.31Accuracy

13

Feb 26, 2026

Food101 5-way 2-shot

64.18Accuracy

13

Feb 26, 2026

Oxford-IIIT Pet 5-way 2-shot

91.44Accuracy

13

Feb 26, 2026

Page 129 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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