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Models/FACT (efficient hybrid of convolution and transformer model)

FACT (efficient hybrid of convolution and transformer model)

Reported on 12 benchmarks across 2 tasks

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

Computer Vision12 results

  • Action LocalizationonBreakfast
    Acc
    76.2
    best: 78 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action LocalizationonBreakfast
    Average F1
    74.7
    best: 76.2 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action LocalizationonBreakfast
    Edit
    79.7
  • Action LocalizationonBreakfast
    F1@10%
    81.4
    best: 82.1 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action LocalizationonBreakfast
    F1@25%
    76.5
    best: 79 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action LocalizationonBreakfast
    F1@50%
    66.2
    best: 67.5 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action SegmentationonBreakfast
    Acc
    76.2
    best: 78 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action SegmentationonBreakfast
    Average F1
    74.7
    best: 76.2 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action SegmentationonBreakfast
    Edit
    79.7
  • Action SegmentationonBreakfast
    F1@10%
    81.4
    best: 82.1 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action SegmentationonBreakfast
    F1@25%
    76.5
    best: 79 (AdaFocus (newly extracted I3D-features, LT-Context model))
  • Action SegmentationonBreakfast
    F1@50%
    66.2
    best: 67.5 (AdaFocus (newly extracted I3D-features, LT-Context model))