TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/RCN - ResNet12

RCN - ResNet12

Reported on 8 benchmarks across 2 tasks · 1 paper

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

Computer Vision8 results

  • Image ClassificationonCIFAR-FS 5-way (1-shot)
    Accuracy· 2020-09-08
    69.02
    best: 89.94 (PT+MAP+SF+SOT (transductive))
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Image ClassificationonMini-Imagenet 5-way (5-shot)
    Accuracy· 2020-09-08
    75.19
    best: 98.72 (SgVA-CLIP)
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Image ClassificationonMini-Imagenet 5-way (1-shot)
    Accuracy· 2020-09-08
    57.4
    best: 97.95 (SgVA-CLIP)
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Image ClassificationonCIFAR-FS 5-way (5-shot)
    Accuracy· 2020-09-08
    82.96
    best: 93.5 (CAML [Laion-2b])
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Few-Shot Image ClassificationonCIFAR-FS 5-way (1-shot)
    Accuracy· 2020-09-08
    69.02
    best: 89.94 (PT+MAP+SF+SOT (transductive))
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Few-Shot Image ClassificationonMini-Imagenet 5-way (5-shot)
    Accuracy· 2020-09-08
    75.19
    best: 98.72 (SgVA-CLIP)
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Few-Shot Image ClassificationonMini-Imagenet 5-way (1-shot)
    Accuracy· 2020-09-08
    57.4
    best: 97.95 (SgVA-CLIP)
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558
  • Few-Shot Image ClassificationonCIFAR-FS 5-way (5-shot)
    Accuracy· 2020-09-08
    82.96
    best: 93.5 (CAML [Laion-2b])
    Region Comparison Network for Interpretable Few-shot Image ClassificationarXiv:2009.03558