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Models/SUM-GAN-AAE

SUM-GAN-AAE

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

  • VideoonTvSum
    F1-score
    58.3
    best: 62 (SegSum)
  • VideoonTvSum
    Parameters (M)
    24.31
    best: 100.76 (CSNet)
  • VideoonTvSum
    training time (s)
    5423
    best: 9380 (AC-SUM-GAN)
  • VideoonSumMe
    F1-score
    48.9
    best: 54.48 (TAC-SUM)
  • VideoonSumMe
    Parameters (M)
    24.31
    best: 100.76 (CSNet)
  • VideoonSumMe
    training time (s)
    1639
    best: 2825 (AC-SUM-GAN)
  • Video SummarizationonTvSum
    F1-score
    58.3
    best: 62 (SegSum)
  • Video SummarizationonTvSum
    Parameters (M)
    24.31
    best: 100.76 (CSNet)
  • Video SummarizationonTvSum
    training time (s)
    5423
    best: 9380 (AC-SUM-GAN)
  • Video SummarizationonSumMe
    F1-score
    48.9
    best: 54.48 (TAC-SUM)
  • Video SummarizationonSumMe
    Parameters (M)
    24.31
    best: 100.76 (CSNet)
  • Video SummarizationonSumMe
    training time (s)
    1639
    best: 2825 (AC-SUM-GAN)