SimpleBaseline3D (ICCV'2017)
```bibtex
@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)
```bibtex
@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 |
| :-------------------------------------------------------------- | :---: | :-----: | :-------------------------------------------------------------: | :------------------------------------------------------------: |
| [SimpleBaseline3D1](/configs/body_3d_keypoint/image_pose_lift/h36m/image-pose-lift_tcn_8xb64-200e_h36m.py) | 43.4 | 34.3 | [ckpt](https://download.openmmlab.com/mmpose/body3d/simple_baseline/simple3Dbaseline_h36m-f0ad73a4_20210419.pth) | [log](https://download.openmmlab.com/mmpose/body3d/simple_baseline/20210415_065056.log.json) |
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.