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Models/UDA

UDA

Reported on 7 benchmarks across 2 tasks · 2 papers · 4 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision7 results

Image ClassificationonImageNet - 10% labeled data
Top 5 Accuracy· 2019-04-29
88.52
best: 92.6 (SimMatch + EPASS (ResNet-50))
SOTA
Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848
Image ClassificationonSVHN, 1000 labels
Accuracy· 2019-04-29
97.54
best: 97.58 (EnAET)
SOTA
Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848
Semi-Supervised Image ClassificationonImageNet - 10% labeled data
Top 5 Accuracy· 2019-04-29
88.52
best: 92.6 (SimMatch + EPASS (ResNet-50))
SOTA
Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848
Semi-Supervised Image ClassificationonSVHN, 1000 labels
Accuracy· 2019-04-29
97.54
best: 97.58 (EnAET)
SOTA
Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848
Image ClassificationonSTL-10
Percentage correct· 2020-01-21
92.34
best: 99.64 (µ2Net+ (ViT-L/16))
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence arXiv:2001.07685
Image ClassificationonCIFAR-10, 4000 Labels
Percentage error· 2019-04-29
5.27
best: 3.96 (SimMatch)
Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848
Semi-Supervised Image ClassificationonCIFAR-10, 4000 Labels
Percentage error· 2019-04-29
5.27
best: 3.96 (SimMatch)
Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848