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Models/FAN (12 points)

FAN (12 points)

Reported on 6 benchmarks across 3 tasks · 1 paper · 3 SOTA

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

Computer Vision2 results

  • Pose EstimationonBIWI
    MAE (trained with other data)· 2017-03-21
    7.882
    best: 2.75 (TRG (w/ 300WLP))
    SOTA
    How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)arXiv:1703.07332
  • Pose EstimationonAFLW2000
    MAE· 2017-03-21
    9.116
    best: 3.15 (OpNet)
    How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)arXiv:1703.07332

Methodology2 results

  • 3DonBIWI
    MAE (trained with other data)· 2017-03-21
    7.882
    best: 2.75 (TRG (w/ 300WLP))
    SOTA
    How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)arXiv:1703.07332
  • 3DonAFLW2000
    MAE· 2017-03-21
    9.116
    best: 3.15 (OpNet)
    How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)arXiv:1703.07332

Audio2 results

  • 1 Image, 2*2 StitchionBIWI
    MAE (trained with other data)· 2017-03-21
    7.882
    best: 2.75 (TRG (w/ 300WLP))
    SOTA
    How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)arXiv:1703.07332
  • 1 Image, 2*2 StitchionAFLW2000
    MAE· 2017-03-21
    9.116
    best: 3.15 (OpNet)
    How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)arXiv:1703.07332