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Models/Dual network

Dual network

Reported on 26 benchmarks across 6 tasks · 1 paper · 12 SOTA

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

Computer Vision14 results

  • 3D Human Pose EstimationonJTA
    F1(t=0.4m)· 2022-05-02
    58.15
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Human Pose EstimationonJTA
    F1(t=0.8m)· 2022-05-02
    69.32
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Human Pose EstimationonJTA
    F1(t=1.2m)· 2022-05-02
    74.19
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • Pose EstimationonJTA
    F1(t=0.4m)· 2022-05-02
    58.15
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • Pose EstimationonJTA
    F1(t=0.8m)· 2022-05-02
    69.32
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • Pose EstimationonJTA
    F1(t=1.2m)· 2022-05-02
    74.19
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Multi-Person Pose Estimation (root-relative)onMuPoTS-3D
    3DPCK· 2022-05-02
    89.6
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Human Pose Estimationon3DPW
    PA-MPJPE· 2022-05-02
    61.7
    best: 157 (Simple-baseline)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Human Pose EstimationonHuman3.6M
    Average MPJPE (mm)· 2022-05-02
    49.31
    best: 131.7 (Rhodin et al.)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Human Pose EstimationonMuPoTS-3D
    3DPCK· 2022-05-02
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • Pose Estimationon3DPW
    PA-MPJPE· 2022-05-02
    61.7
    best: 157 (Simple-baseline)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • Pose EstimationonHuman3.6M
    Average MPJPE (mm)· 2022-05-02
    49.31
    best: 131.7 (Rhodin et al.)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • Pose EstimationonMuPoTS-3D
    3DPCK· 2022-05-02
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3D Multi-Person Pose EstimationonMuPoTS-3D
    3DPCK· 2022-05-02
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748

Methodology6 results

  • 3DonJTA
    F1(t=0.4m)· 2022-05-02
    58.15
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3DonJTA
    F1(t=0.8m)· 2022-05-02
    69.32
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3DonJTA
    F1(t=1.2m)· 2022-05-02
    74.19
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3Don3DPW
    PA-MPJPE· 2022-05-02
    61.7
    best: 157 (Simple-baseline)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3DonHuman3.6M
    Average MPJPE (mm)· 2022-05-02
    49.31
    best: 131.7 (Rhodin et al.)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 3DonMuPoTS-3D
    3DPCK· 2022-05-02
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748

Audio6 results

  • 1 Image, 2*2 StitchionJTA
    F1(t=0.4m)· 2022-05-02
    58.15
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 1 Image, 2*2 StitchionJTA
    F1(t=0.8m)· 2022-05-02
    69.32
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 1 Image, 2*2 StitchionJTA
    F1(t=1.2m)· 2022-05-02
    74.19
    SOTA
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 1 Image, 2*2 Stitchion3DPW
    PA-MPJPE· 2022-05-02
    61.7
    best: 157 (Simple-baseline)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 1 Image, 2*2 StitchionHuman3.6M
    Average MPJPE (mm)· 2022-05-02
    49.31
    best: 131.7 (Rhodin et al.)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748
  • 1 Image, 2*2 StitchionMuPoTS-3D
    3DPCK· 2022-05-02
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Dual networks based 3D Multi-Person Pose Estimation from Monocular VideoarXiv:2205.00748