提交 259a2909 编写于 作者: D Dario Pavllo

Update README

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<p align="center"><img src="images/convolutions_anim.gif" width="50%" alt="" /></p>
This is the implementation of the approach described in the paper:
> Dario Pavllo, Christoph Feichtenhofer, David Grangier, and Michael Auli. [3D human pose estimation in video with temporal convolutions and semi-supervised training](https://arxiv.org/abs/1811.11742). In *arXiv*, 2018.
> Dario Pavllo, Christoph Feichtenhofer, David Grangier, and Michael Auli. [3D human pose estimation in video with temporal convolutions and semi-supervised training](https://arxiv.org/abs/1811.11742). In Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
More demos are available at https://dariopavllo.github.io/VideoPose3D
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This work is licensed under CC BY-NC. See LICENSE for details. Third-party datasets are subject to their respective licenses.
If you use our code/models in your research, please cite our paper:
```
@article{pavllo:videopose3d:2018,
@inproceedings{pavllo:videopose3d:2019,
title={3D human pose estimation in video with temporal convolutions and semi-supervised training},
author={Pavllo, Dario and Feichtenhofer, Christoph and Grangier, David and Auli, Michael},
journal={arXiv},
volume={abs/1811.11742},
year={2018}
booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}
```
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