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|![repro](doc/feng/repro_512.gif)|![smpl](doc/feng/smpl_512.gif)|
> The following codes are not released. We are now working hard on them.
> The following features are not released yet. We are now working hard on them. Please stay tuned!
- [ ] Whole body 3d keypoints estimation
- [ ] SMPL-H/SMPLX support
- [ ] Detailed mesh from sparse view. An alternative way to obtain the detailed mesh is using [Neural Body](https://zju3dv.github.io/neuralbody/).
- [ ] Dense reconstruction and view synthesis from sparse view: [Neural Body](https://zju3dv.github.io/neuralbody/).
|:black_square_button: Whole Body|:black_square_button: [Detailed Mesh](https://zju3dv.github.io/neuralbody/)|
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@ -132,19 +132,21 @@ The data in `smpl/000000.json` is also a list, each element represents the SMPL
We set the first 3 dimensions of `poses` to zero, and add a new parameter `Rh` to represents the global oritentation, the vertices of SMPL model V = RX(theta, beta) + T.
## Acknowledgements
Here are some great resources we benefit:
Here are the great works this project is built upon:
- SMPL models and layer is borrowed from MPII [SMPL-X model](https://github.com/vchoutas/smplx).
- SMPL models and layer are from MPII [SMPL-X model](https://github.com/vchoutas/smplx).
- Some functions are borrowed from [SPIN](https://github.com/nkolot/SPIN), [VIBE](https://github.com/mkocabas/VIBE), [SMPLify-X](https://github.com/vchoutas/smplify-x)
- Our project is similar with [TotalCapture](http://www.cs.cmu.edu/~hanbyulj/totalcapture/)
- The method for fitting 3D skeleton and SMPL model is similar with [TotalCapture](http://www.cs.cmu.edu/~hanbyulj/totalcapture/), without using point cloud.
We also would like to thank Wenduo Feng for the example data.
We also would like to thank Wenduo Feng who is the performer in the sample data.
## Contact
Please open an issue if you have any questions.
## Citation
This project is the base of our other works: [iMocap](https://zju3dv.github.io/iMoCap/), [Neural Body](https://zju3dv.github.io/neuralbody/)
This project is a part of our work [iMocap](https://zju3dv.github.io/iMoCap/) and [Neural Body](https://zju3dv.github.io/neuralbody/)
Please consider citing these works if you find this repo is useful for your projects.
```bibtex
@inproceedings{dong2020motion,