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Models/PI-Net

PI-Net

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 Vision4 results

3D Multi-Person Pose Estimation (root-relative)onMuPoTS-3D
3DPCK· 2020-10-11
82.5
best: 89.6 (TDBU_Net)
PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation arXiv:2010.05302
3D Human Pose EstimationonMuPoTS-3D
3DPCK· 2020-10-11
82.5
best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation arXiv:2010.05302
Pose EstimationonMuPoTS-3D
3DPCK· 2020-10-11
82.5
best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation arXiv:2010.05302
3D Multi-Person Pose EstimationonMuPoTS-3D
3DPCK· 2020-10-11
82.5
best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation arXiv:2010.05302

Methodology1 result

3DonMuPoTS-3D
3DPCK· 2020-10-11
82.5
best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation arXiv:2010.05302

Audio1 result

1 Image, 2*2 StitchionMuPoTS-3D
3DPCK· 2020-10-11
82.5
best: 89.9 (Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement)
PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation arXiv:2010.05302