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Models/AMC-Net

AMC-Net

Reported on 10 benchmarks across 2 tasks

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

Computer Vision10 results

  • VideoonDAVIS 2016 val
    F
    84.6
    best: 90.2 (DEVA (DIS))
  • VideoonDAVIS 2016 val
    G
    84.6
    best: 88.9 (GSANet)
  • VideoonDAVIS 2016 val
    J
    84.5
    best: 88.3 (GSANet)
  • VideoonYouTube-Objects
    J
    71.1
    best: 75.1 (FakeFlow)
  • VideoonFBMS test
    J
    76.5
    best: 84.7 (FakeFlow)
  • Video Object SegmentationonDAVIS 2016 val
    F
    84.6
    best: 90.2 (DEVA (DIS))
  • Video Object SegmentationonDAVIS 2016 val
    G
    84.6
    best: 88.9 (GSANet)
  • Video Object SegmentationonDAVIS 2016 val
    J
    84.5
    best: 88.3 (GSANet)
  • Video Object SegmentationonYouTube-Objects
    J
    71.1
    best: 75.1 (FakeFlow)
  • Video Object SegmentationonFBMS test
    J
    76.5
    best: 84.7 (FakeFlow)