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Benchmarks for “image classification”

Compare state-of-the-art methods across the tasks and datasets used to measure AI progress.

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TaskDatasetDomainTrendResultsLast update
Image ClassificationEMNIST mnist 10 classescomputer vision6Feb 26, 2026
Image ClassificationCaltech101 (val)computer vision6Feb 26, 2026
Image ClassificationImageNet (test)computer vision6Feb 26, 2026
Image ClassificationMini-ImageNetcomputer vision6Feb 26, 2026
Image ClassificationCIFAR10computer vision6Feb 26, 2026
Image ClassificationFMNISTcomputer vision6Feb 26, 2026
Image ClassificationCIFAR-100 (test)computer vision6Feb 26, 2026
Image ClassificationDTDcomputer vision6Feb 26, 2026
Image ClassificationCIFAR10 Noise ratio 0.6, Open ratio 1.0 (test)computer vision6Feb 26, 2026
Image ClassificationCIFAR10 Noise ratio 0.6, Open ratio 0.5 (test)computer vision6Feb 26, 2026
Image ClassificationCIFAR10 Noise ratio 0.3, Open ratio 1.0 (test)computer vision6Feb 26, 2026
Image ClassificationCIFAR10 Noise ratio 0.3, Open ratio 0.5 (test)computer vision6Feb 26, 2026
Image ClassificationImageNet-100 (40-20 split)computer vision6Feb 26, 2026
Image ClassificationImageNet-100 (60-20 split)computer vision6Feb 26, 2026
Image ClassificationImageNet-100 (80-20 split)computer vision6Feb 26, 2026
Image ClassificationImageNet-100 (100-20 split)computer vision6Feb 26, 2026
Image ClassificationOfficeHome cross-domaincomputer vision6Feb 26, 2026
Image ClassificationRSNAcomputer vision6Feb 26, 2026
Image ClassificationCIFAR-100computer vision6Feb 26, 2026
Image ClassificationMS-Celeb-1Mcomputer vision6Feb 26, 2026
Image ClassificationCASIAcomputer vision6Feb 26, 2026
Image ClassificationTiny-ImageNet-200computer vision6Feb 26, 2026
Image ClassificationOFFICE-31 (US)computer vision6Feb 26, 2026
Image ClassificationOFFICE-31 (UL)computer vision6Feb 26, 2026
Image ClassificationOFFICE-31 (L)computer vision6Feb 26, 2026