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/Fast-RCNN

Fast-RCNN

Reported on 8 benchmarks across 1 task · 1 paper · 7 SOTA

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

Computer Vision8 results

  • Object CountingonPascal VOC 2007 count-test
    m-reIRMSE-nz· 2016-04-12
    0.85
    best: 0.61 (Supervised Density Map)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonPascal VOC 2007 count-test
    m-relRMSE· 2016-04-12
    0.26
    best: 0.17 (Supervised Density Map)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonPascal VOC 2007 count-test
    mRMSE-nz· 2016-04-12
    1.92
    best: 0.009 (Omnicount)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonCOCO count-test
    m-reIRMSE· 2016-04-12
    0.2
    best: 0.18 (ens)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonCOCO count-test
    m-reIRMSE-nz· 2016-04-12
    1.13
    best: 0.81 (ens)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonCOCO count-test
    mRMSE· 2016-04-12
    0.49
    best: 0.34 (Supervised Density Map)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonCOCO count-test
    mRMSE-nz· 2016-04-12
    2.78
    best: 1.89 (Supervised Density Map)
    SOTA
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505
  • Object CountingonPascal VOC 2007 count-test
    mRMSE· 2016-04-12
    0.5
    best: 0.0023 (Omnicount)
    Counting Everyday Objects in Everyday ScenesarXiv:1604.03505