amos-zq / realtime_multi-person_pose_estimation

Code repo for realtime multi-person pose estimation, without using any person detector.

Realtime Multi-Person Pose Estimation

By Zhe Cao, Tomas Simon, Shih-En Wei, Yaser Sheikh.

Introduction

Code repo for winning 2016 MSCOCO Keypoints Challenge, ECCV Best Demo Award.

Watch our [video result] (https://www.youtube.com/watch?v=pW6nZXeWlGM&t=77s) on funny Youtube videos.

We present a bottom-up approach for multi-person pose estimation, without using any person detector. For more details, refer to our Arxiv paper and presentation slides at ILSVRC and COCO workshop 2016.

This project is licensed under the terms of the GPL v3 license .

Contact: Zhe Cao Email: [email protected]

Results

Contents

1. Testing
2. Training
3. Citation

Testing

C++ (realtime version)

• Use our modified caffe: caffe_demo. Follow the instruction on that repo.
• Three input options: images, video, webcam

Matlab (slower)

• Compatible with general Caffe. Compile matcaffe.
• Run cd testing; get_model.sh to retreive our latest MSCOCO model from our web server.
• Change the caffepath in the config.m and run demo.m for an example usage.

Python

• iPython Notebook documentation will be released soon!

Training

• Network Architecture

• Code will be released soon!

Related repository

CVPR'16, Convolutional Pose Machines

Citation

Please cite the paper in your publications if it helps your research:

@article{cao2016realtime,
  title={Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields},
  author={Zhe Cao and Tomas Simon and Shih-En Wei and Yaser Sheikh},
  journal={arXiv preprint arXiv:1611.08050},
  year={2016}
  }
  
@inproceedings{wei2016cpm,
  author = {Shih-En Wei and Varun Ramakrishna and Takeo Kanade and Yaser Sheikh},
  booktitle = {CVPR},
  title = {Convolutional pose machines},
  year = {2016}
  }