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Body(3D,Kpt,Img)




H36m Dataset


Pose Lift + Simplebaseline3d on H36m

SimpleBaseline3D (ICCV'2017)
@inproceedings{martinez_2017_3dbaseline,
  title={A simple yet effective baseline for 3d human pose estimation},
  author={Martinez, Julieta and Hossain, Rayat and Romero, Javier and Little, James J.},
  booktitle={ICCV},
  year={2017}
}
Human3.6M (TPAMI'2014)
@article{h36m_pami,
  author = {Ionescu, Catalin and Papava, Dragos and Olaru, Vlad and Sminchisescu,  Cristian},
  title = {Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
  publisher = {IEEE Computer Society},
  volume = {36},
  number = {7},
  pages = {1325-1339},
  month = {jul},
  year = {2014}
}

Results on Human3.6M dataset with ground truth 2D detections

Arch MPJPE P-MPJPE ckpt log
simple_baseline_3d_tcn1 43.4 34.3 ckpt log

1 Differing from the original paper, we didn’t apply the max-norm constraint because we found this led to a better convergence and performance.




Mpi_inf_3dhp Dataset


Pose Lift + Simplebaseline3d on Mpi_inf_3dhp

SimpleBaseline3D (ICCV'2017)
@inproceedings{martinez_2017_3dbaseline,
  title={A simple yet effective baseline for 3d human pose estimation},
  author={Martinez, Julieta and Hossain, Rayat and Romero, Javier and Little, James J.},
  booktitle={ICCV},
  year={2017}
}
MPI-INF-3DHP (3DV'2017)
@inproceedings{mono-3dhp2017,
  author = {Mehta, Dushyant and Rhodin, Helge and Casas, Dan and Fua, Pascal and Sotnychenko, Oleksandr and Xu, Weipeng and Theobalt, Christian},
  title = {Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision},
  booktitle = {3D Vision (3DV), 2017 Fifth International Conference on},
  url = {http://gvv.mpi-inf.mpg.de/3dhp_dataset},
  year = {2017},
  organization={IEEE},
  doi={10.1109/3dv.2017.00064},
}

Results on MPI-INF-3DHP dataset with ground truth 2D detections

Arch MPJPE P-MPJPE 3DPCK 3DAUC ckpt log
simple_baseline_3d_tcn1 84.3 53.2 85.0 52.0 ckpt log

1 Differing from the original paper, we didn’t apply the max-norm constraint because we found this led to a better convergence and performance.

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