TasksSotADatasetsPapersMethodsSubmitAbout
Papers With Code 2

A community resource for machine learning research: papers, code, benchmarks, and state-of-the-art results.

Explore

Notable BenchmarksAll SotADatasetsPapersMethods

Community

Submit ResultsAbout

Data sourced from the PWC Archive (CC-BY-SA 4.0). Built by the community, for the community.

Models/TDBU_Net

TDBU_Net

Reported on 7 benchmarks across 7 tasks · 1 paper · 7 SOTA

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

Computer Vision8 results

  • 3D Multi-Person Pose Estimation (root-relative)onMuPoTS-3D
    3DPCK· 2021-04-05
    89.6
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 3D Human Pose EstimationonMuPoTS-3D
    3DPCK· 2021-04-05
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 3D Multi-Person Pose Estimation (absolute)onMuPoTS-3D
    3DPCK· 2021-04-05
    48
    best: 50.9 (POTR-3D)
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • Pose EstimationonMuPoTS-3D
    3DPCK· 2021-04-05
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 3D Multi-Person Pose EstimationonMuPoTS-3D
    3DPCK· 2021-04-05
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 3D Human Pose EstimationonMuPoTS-3D
    3DPCK· 2021-04-05
    48
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • Pose EstimationonMuPoTS-3D
    3DPCK· 2021-04-05
    48
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 3D Multi-Person Pose EstimationonMuPoTS-3D
    3DPCK· 2021-04-05
    48
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797

Methodology2 results

  • 3DonMuPoTS-3D
    3DPCK· 2021-04-05
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 3DonMuPoTS-3D
    3DPCK· 2021-04-05
    48
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797

Audio2 results

  • 1 Image, 2*2 StitchionMuPoTS-3D
    3DPCK· 2021-04-05
    89.6
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    SOTA
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797
  • 1 Image, 2*2 StitchionMuPoTS-3D
    3DPCK· 2021-04-05
    48
    best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
    Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up NetworksarXiv:2104.01797