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Models/MT-ArcVGG

MT-ArcVGG

Reported on 6 benchmarks across 6 tasks · 1 paper

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

Computer Vision3 results

  • Face ReconstructiononRAF-DB
    Avg. Accuracy· 2019-09-25
    76
    best: 87.5 (C-EXPR-NET)
    Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacearXiv:1910.04855
  • Facial Expression Recognition (FER)onRAF-DB
    Avg. Accuracy· 2019-09-25
    76
    best: 87.5 (C-EXPR-NET)
    Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacearXiv:1910.04855
  • 3D Face ReconstructiononRAF-DB
    Avg. Accuracy· 2019-09-25
    76
    best: 87.5 (C-EXPR-NET)
    Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacearXiv:1910.04855

Music1 result

  • Facial Recognition and ModellingonRAF-DB
    Avg. Accuracy· 2019-09-25
    76
    best: 87.5 (C-EXPR-NET)
    Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacearXiv:1910.04855

Methodology1 result

  • 3DonRAF-DB
    Avg. Accuracy· 2019-09-25
    76
    best: 87.5 (C-EXPR-NET)
    Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacearXiv:1910.04855

Medical1 result

  • 3D Face ModellingonRAF-DB
    Avg. Accuracy· 2019-09-25
    76
    best: 87.5 (C-EXPR-NET)
    Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFacearXiv:1910.04855