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/F2Net

F2Net

Reported on 8 benchmarks across 2 tasks · 1 paper · 2 SOTA

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

Computer Vision8 results

  • VideoonFBMS test
    J· 2020-12-04
    77.5
    best: 84.7 (FakeFlow)
    SOTA
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • Video Object SegmentationonFBMS test
    J· 2020-12-04
    77.5
    best: 84.7 (FakeFlow)
    SOTA
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • VideoonDAVIS 2016 val
    F· 2020-12-04
    54.4
    best: 90.2 (DEVA (DIS))
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • VideoonDAVIS 2016 val
    G· 2020-12-04
    83.7
    best: 88.9 (GSANet)
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • VideoonDAVIS 2016 val
    J· 2020-12-04
    83.1
    best: 88.3 (GSANet)
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • Video Object SegmentationonDAVIS 2016 val
    F· 2020-12-04
    54.4
    best: 90.2 (DEVA (DIS))
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • Video Object SegmentationonDAVIS 2016 val
    G· 2020-12-04
    83.7
    best: 88.9 (GSANet)
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534
  • Video Object SegmentationonDAVIS 2016 val
    J· 2020-12-04
    83.1
    best: 88.3 (GSANet)
    F2Net: Learning to Focus on the Foreground for Unsupervised Video Object SegmentationarXiv:2012.02534