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Models/Seesaw-shuffleFaceNet(mobi)

Seesaw-shuffleFaceNet(mobi)

Reported on 36 benchmarks across 6 tasks · 1 paper · 31 SOTA

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

Computer Vision12 results

  • Face ReconstructiononAgeDB-30
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face ReconstructiononCFP-FP
    Accuracy· 2019-08-24
    0.9307
    best: 0.9951 (PartialFC (R200))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face ReconstructiononCFP-FP
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face ReconstructiononLFW
    Accuracy· 2019-08-24
    0.9965
    best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face ReconstructiononLFW
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ReconstructiononAgeDB-30
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ReconstructiononCFP-FP
    Accuracy· 2019-08-24
    0.9307
    best: 0.9951 (PartialFC (R200))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ReconstructiononCFP-FP
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ReconstructiononLFW
    Accuracy· 2019-08-24
    0.9965
    best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ReconstructiononLFW
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face ReconstructiononAgeDB-30
    Accuracy· 2019-08-24
    0.9648
    best: 71.62 (USynthFace)
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ReconstructiononAgeDB-30
    Accuracy· 2019-08-24
    0.9648
    best: 71.62 (USynthFace)
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124

Methodology12 results

  • Face RecognitiononAgeDB-30
    Accuracy· 2019-08-24
    0.9648
    best: 71.62 (USynthFace)
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face RecognitiononAgeDB-30
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face RecognitiononCFP-FP
    Accuracy· 2019-08-24
    0.9307
    best: 0.9933 (GhostFaceNetV2-1)
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face RecognitiononCFP-FP
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face RecognitiononLFW
    Accuracy· 2019-08-24
    0.9965
    best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Face RecognitiononLFW
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3DonAgeDB-30
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3DonCFP-FP
    Accuracy· 2019-08-24
    0.9307
    best: 0.9951 (PartialFC (R200))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3DonCFP-FP
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3DonLFW
    Accuracy· 2019-08-24
    0.9965
    best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3DonLFW
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3DonAgeDB-30
    Accuracy· 2019-08-24
    0.9648
    best: 71.62 (USynthFace)
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124

Music6 results

  • Facial Recognition and ModellingonAgeDB-30
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Facial Recognition and ModellingonCFP-FP
    Accuracy· 2019-08-24
    0.9307
    best: 0.9951 (PartialFC (R200))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Facial Recognition and ModellingonCFP-FP
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Facial Recognition and ModellingonLFW
    Accuracy· 2019-08-24
    0.9965
    best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Facial Recognition and ModellingonLFW
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • Facial Recognition and ModellingonAgeDB-30
    Accuracy· 2019-08-24
    0.9648
    best: 71.62 (USynthFace)
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124

Medical6 results

  • 3D Face ModellingonAgeDB-30
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ModellingonCFP-FP
    Accuracy· 2019-08-24
    0.9307
    best: 0.9951 (PartialFC (R200))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ModellingonCFP-FP
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ModellingonLFW
    Accuracy· 2019-08-24
    0.9965
    best: 0.998667 (GhostFaceNetV2-1 (MS1MV3))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ModellingonLFW
    MParams· 2019-08-24
    2.8
    best: 3.65 (EdgeFace - S (g=0.5))
    SOTA
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124
  • 3D Face ModellingonAgeDB-30
    Accuracy· 2019-08-24
    0.9648
    best: 71.62 (USynthFace)
    SeesawFaceNets: sparse and robust face verification model for mobile platformarXiv:1908.09124