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Models/AMP

AMP

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

  • VideoonYouTube-Objects
    J· 2023-03-18
    75
    best: 75.1 (FakeFlow)
    SOTA
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • Video Object SegmentationonYouTube-Objects
    J· 2023-03-18
    75
    best: 75.1 (FakeFlow)
    SOTA
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • VideoonDAVIS 2016 val
    F· 2023-03-18
    87.5
    best: 90.2 (DEVA (DIS))
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • VideoonDAVIS 2016 val
    G· 2023-03-18
    87.3
    best: 88.9 (GSANet)
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • VideoonDAVIS 2016 val
    J· 2023-03-18
    87.1
    best: 88.3 (GSANet)
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • Video Object SegmentationonDAVIS 2016 val
    F· 2023-03-18
    87.5
    best: 90.2 (DEVA (DIS))
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • Video Object SegmentationonDAVIS 2016 val
    G· 2023-03-18
    87.3
    best: 88.9 (GSANet)
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383
  • Video Object SegmentationonDAVIS 2016 val
    J· 2023-03-18
    87.1
    best: 88.3 (GSANet)
    Adaptive Multi-source Predictor for Zero-shot Video Object SegmentationarXiv:2303.10383