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Models/EAC(ResNet-50)

EAC(ResNet-50)

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 ReconstructiononRAF-DB
    Overall Accuracy· 2022-07-21
    90.35
    best: 94.76 (ResEmoteNet)
    SOTA
    Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionarXiv:2207.10299
  • Facial Expression Recognition (FER)onRAF-DB
    Overall Accuracy· 2022-07-21
    90.35
    best: 94.76 (ResEmoteNet)
    SOTA
    Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionarXiv:2207.10299
  • 3D Face ReconstructiononRAF-DB
    Overall Accuracy· 2022-07-21
    90.35
    best: 94.76 (ResEmoteNet)
    SOTA
    Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionarXiv:2207.10299

Music1 result

  • Facial Recognition and ModellingonRAF-DB
    Overall Accuracy· 2022-07-21
    90.35
    best: 94.76 (ResEmoteNet)
    SOTA
    Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionarXiv:2207.10299

Methodology1 result

  • 3DonRAF-DB
    Overall Accuracy· 2022-07-21
    90.35
    best: 94.76 (ResEmoteNet)
    SOTA
    Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionarXiv:2207.10299

Medical1 result

  • 3D Face ModellingonRAF-DB
    Overall Accuracy· 2022-07-21
    90.35
    best: 94.76 (ResEmoteNet)
    SOTA
    Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression RecognitionarXiv:2207.10299