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Papers Benchmarks Datasets Tasks

Image Classification research benchmarks – Page 165 · SOTA2 Research

Image Classification

Benchmarks

Dataset NameSOTA MethodSort

Dataset NameSOTA methodMetricTrendResultsLast Updated

CIFAR100 16/255 noise (test)

50.76Natural Accuracy

10

Feb 26, 2026

CIFAR100 12/255 noise (test)

53.46Natural Accuracy

10

Feb 26, 2026

CIFAR100 8/255 noise (test)

60.29Natural Accuracy

10

Feb 26, 2026

CIFAR10 32/255 noise (test)

70.84Natural Accuracy

10

Feb 26, 2026

CIFAR10 16/255 noise (test)

82.98Natural Accuracy

10

Feb 26, 2026

CIFAR10 12/255 noise (test)

81.09Natural Accuracy

10

Feb 26, 2026

CIFAR10 8/255 noise (test)

85.07Natural Accuracy

10

Feb 26, 2026

46.95Robust Acc (8/255)

10

Feb 26, 2026

Average (Flowers102, OxfordPets, VOC2007) (test)

94.041Top-1 Accuracy

10

Feb 26, 2026

Dogs-120 (test)

86.31Top-1 Accuracy

10

Feb 26, 2026

1.51Latency (ms)

10

Feb 26, 2026

ImageNet (test)

79.18Accuracy

10

Feb 26, 2026

ImageNet-1K (val)

75.4Top-1 Accuracy

10

Feb 26, 2026

CLIP Embeddings-H

79.4Accuracy

10

Feb 26, 2026

CLIP Embeddings-H

81.9Accuracy

10

Feb 26, 2026

Waterbirds (test)

Intrinsic Feature Guidance

63.64Avg Acc (0.5% Bias)

10

Feb 26, 2026

ImageNet (Source) and 10 Target Datasets (SUN397, Aircraft, EuroSAT, StanfordCars, Food101, Pets, Flower102, Caltech101, DTD, UCF101) 16-shot (train)

76.9ImageNet Source Accuracy

10

Feb 26, 2026

FMoW WILDS (test)

46.4WC Accuracy

10

Feb 26, 2026

84.4Zero-shot Accuracy

10

Feb 26, 2026

CUB-200 x8 2011 (test)

78.3Top-1 Accuracy

10

Feb 26, 2026

CUB-200 2011 x4 (test)

0.783Top-1 Accuracy

10

Feb 26, 2026

StanfordCars x8 (test)

0.864Top-1 Accuracy

10

Feb 26, 2026

StanfordCars x4 (test)

86.4Top-1 Accuracy

10

Feb 26, 2026

ImageNet Source 1K (test)

76.5Accuracy

10

Feb 26, 2026

ImageNet (test)

77.35Accuracy

10

Feb 26, 2026

Page 165 of 333

Popular datasets

CIFAR ImageNet MNIST CIFAR-10 CIFAR-100

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