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Models/ReMixMatch

ReMixMatch

Reported on 15 benchmarks across 2 tasks · 3 papers · 8 SOTA

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

Computer Vision15 results

  • Image ClassificationonCIFAR-100, 400 Labels
    Percentage error· 2022-08-12
    16.8
    best: 15.62 (SemiReward)
    SOTA
    USB: A Unified Semi-supervised Learning Benchmark for ClassificationarXiv:2208.07204
  • Semi-Supervised Image ClassificationonCIFAR-100, 400 Labels
    Percentage error· 2022-08-12
    16.8
    best: 15.62 (SemiReward)
    SOTA
    USB: A Unified Semi-supervised Learning Benchmark for ClassificationarXiv:2208.07204
  • Image ClassificationonSTL-10, 1000 Labels
    Accuracy· 2019-11-21
    93.82
    best: 94.53 (NP-Match)
    SOTA
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Image Classificationoncifar10, 250 Labels
    Percentage correct· 2019-11-21
    93.73
    SOTA
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Image ClassificationonCIFAR-10, 250 Labels
    Percentage error· 2019-11-21
    6.27
    best: 3.47 (SemiOccam)
    SOTA
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Semi-Supervised Image ClassificationonSTL-10, 1000 Labels
    Accuracy· 2019-11-21
    93.82
    best: 94.53 (NP-Match)
    SOTA
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Semi-Supervised Image Classificationoncifar10, 250 Labels
    Percentage correct· 2019-11-21
    93.73
    SOTA
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Semi-Supervised Image ClassificationonCIFAR-10, 250 Labels
    Percentage error· 2019-11-21
    6.27
    best: 3.47 (SemiOccam)
    SOTA
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Image ClassificationonSTL-10
    Percentage correct· 2020-01-21
    94.77
    best: 99.64 (µ2Net+ (ViT-L/16))
    FixMatch: Simplifying Semi-Supervised Learning with Consistency and ConfidencearXiv:2001.07685
  • Image ClassificationonCIFAR-10, 4000 Labels
    Percentage error· 2019-11-21
    5.14
    best: 3.96 (SimMatch)
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Image ClassificationonSVHN, 1000 labels
    Accuracy· 2019-11-21
    97.17
    best: 97.58 (EnAET)
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Image ClassificationonCIFAR-10, 40 Labels
    Percentage error· 2019-11-21
    19.1
    best: 3.51 (SemiOccam)
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Semi-Supervised Image ClassificationonCIFAR-10, 4000 Labels
    Percentage error· 2019-11-21
    5.14
    best: 3.96 (SimMatch)
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Semi-Supervised Image ClassificationonSVHN, 1000 labels
    Accuracy· 2019-11-21
    97.17
    best: 97.58 (EnAET)
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785
  • Semi-Supervised Image ClassificationonCIFAR-10, 40 Labels
    Percentage error· 2019-11-21
    19.1
    best: 3.51 (SemiOccam)
    ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation AnchoringarXiv:1911.09785