https://github.com/haofanwang/accurate-head-pose

Pytorch code for Hybrid Coarse-fine Classification for Head Pose Estimation
https://github.com/haofanwang/accurate-head-pose

head-pose-estimation headpose pytorch

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Pytorch code for Hybrid Coarse-fine Classification for Head Pose Estimation

• Host: GitHub
• URL: https://github.com/haofanwang/accurate-head-pose
• Owner: haofanwang
• Created: 2019-01-30T09:59:07.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-09-22T22:49:30.000Z (about 4 years ago)
• Last Synced: 2023-03-05T11:44:07.001Z (over 1 year ago)
• Topics: head-pose-estimation, headpose, pytorch
• Language: Python
• Homepage:
• Size: 730 KB
• Stars: 96
• Watchers: 4
• Forks: 22
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# accurate-head-pose

We release the code of the [Hybrid Coarse-fine Classification for Head Pose Estimation](https://arxiv.org/abs/1901.06778), built on top of the [deep-head-pose](https://github.com/natanielruiz/deep-head-pose).

### Pretrained model

We provide pretrained model to reproduce the same result shown in the paper.  

[AFLW2000](https://pan.baidu.com/s/1y9q0JmnA-QxaORyn5fhPKQ), password: drmz  

[AFLW](https://pan.baidu.com/s/1rj2xLINrabaqiIzvSKlGEg), password: yym5  

[BIWI](https://pan.baidu.com/s/1bZXMdGiycX4T4u0VVofQXQ), password: 8qpc  

For those who cannot have access to BaiduDisk, you can download pretrained models on [Google Drive](https://drive.google.com/drive/folders/1is55mbFHsAVbeStkIZf9LV4HdiSjJHd9?usp=sharing)

### Testing

Training and testing lists can be found in /tools, you need download corresonding dataset and update the path.  

[AFLW2000 dataset](https://pan.baidu.com/s/1GMyAC0I_x79zXmXIegpaQg), password: xr6e  

```bash

python test_hopenet.py --gpu 0 --data_dir directory-path-for-dataset --filename_list filename-list --snapshot model --dataset dataset-name 

```

### TODO

Instructions for scripts  

Better and better models  

Videos and example demo  

### Cite this work

Haofan Wang, Zhenhua Chen and Yi Zhou "Hybrid coarse-fine classification for head pose estimation." arXiv:1901.06778, 2019. ([Download](https://arxiv.org/abs/1901.06778))

Biblatex entry:

            @article{wang2019hybrid,

              title={Hybrid coarse-fine classification for head pose estimation},

              author={Wang, Haofan and Chen, Zhenghua and Zhou, Yi},

              journal={arXiv preprint arXiv:1901.06778},

              year={2019}

            }

            

### Acknowledgement

Our hybrid classification network is plug-and-play on top of the [deep-head-pose](https://github.com/natanielruiz/deep-head-pose), but it could be extended to other classification tasks easily. We thank Nataniel Ruiz for releasing deep-head-pose-Pytorch codebase.