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/RGMP (val)

RGMP (val)

Reported on 9 benchmarks across 3 tasks · 1 paper

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

Computer Vision9 results

  • VideoonDAVIS 2016
    F-measure (Mean)· 2020-07-11
    68.9
    best: 94.7 (SwinB-DeAOT-L)
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • VideoonDAVIS 2016
    J&F· 2020-07-11
    68.8
    best: 93.4 (ISVOS (BL30K, MS))
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • VideoonDAVIS 2016
    Jaccard (Mean)· 2020-07-11
    68.6
    best: 92.5 (ISVOS (BL30K, MS))
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • Video Object SegmentationonDAVIS 2016
    F-measure (Mean)· 2020-07-11
    68.9
    best: 94.7 (SwinB-DeAOT-L)
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • Video Object SegmentationonDAVIS 2016
    J&F· 2020-07-11
    68.8
    best: 93.4 (ISVOS (BL30K, MS))
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· 2020-07-11
    68.6
    best: 92.5 (ISVOS (BL30K, MS))
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    F-measure (Mean)· 2020-07-11
    68.9
    best: 94.7 (SwinB-DeAOT-L)
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    J&F· 2020-07-11
    68.8
    best: 93.4 (ISVOS (BL30K, MS))
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687
  • Semi-Supervised Video Object SegmentationonDAVIS 2016
    Jaccard (Mean)· 2020-07-11
    68.6
    best: 92.5 (ISVOS (BL30K, MS))
    Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template MatchingarXiv:2007.05687