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Models/PPDN

PPDN

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

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

Computer Vision3 results

  • Face ReconstructiononOulu-CASIA
    Accuracy (10-fold)· 2016-07-24
    84.59
    best: 89.6 (Dynamic MTL)
    SOTA
    Peak-Piloted Deep Network for Facial Expression RecognitionarXiv:1607.06997
  • Facial Expression Recognition (FER)onOulu-CASIA
    Accuracy (10-fold)· 2016-07-24
    84.59
    best: 89.6 (Dynamic MTL)
    SOTA
    Peak-Piloted Deep Network for Facial Expression RecognitionarXiv:1607.06997
  • 3D Face ReconstructiononOulu-CASIA
    Accuracy (10-fold)· 2016-07-24
    84.59
    best: 89.6 (Dynamic MTL)
    SOTA
    Peak-Piloted Deep Network for Facial Expression RecognitionarXiv:1607.06997

Music1 result

  • Facial Recognition and ModellingonOulu-CASIA
    Accuracy (10-fold)· 2016-07-24
    84.59
    best: 89.6 (Dynamic MTL)
    SOTA
    Peak-Piloted Deep Network for Facial Expression RecognitionarXiv:1607.06997

Methodology1 result

  • 3DonOulu-CASIA
    Accuracy (10-fold)· 2016-07-24
    84.59
    best: 89.6 (Dynamic MTL)
    SOTA
    Peak-Piloted Deep Network for Facial Expression RecognitionarXiv:1607.06997

Medical1 result

  • 3D Face ModellingonOulu-CASIA
    Accuracy (10-fold)· 2016-07-24
    84.59
    best: 89.6 (Dynamic MTL)
    SOTA
    Peak-Piloted Deep Network for Facial Expression RecognitionarXiv:1607.06997