Human Pose Estimation with Parsing Induced Learner

This repository contains the code and pretrained models of

Human Pose Estimation with Parsing Induced Learner [PDF]
Xuecheng Nie, Jiashi Feng, Yiming Zuo, and Shuicheng Yan
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018

Prerequisites

• Python 3.5
• Pytorch 0.2.0
• OpenCV 3.0 or higher

Installation

1. Install Pytorch: Please follow the official instruction on installation of Pytorch.
2. Clone the repository

   git clone --recursive https://github.com/NieXC/pytorch-pil.git
   

3. Download Look into Person (LIP) dataset and create symbolic links to the following directories

   ln -s PATH_TO_LIP_TRAIN_IMAGES_DIR dataset/lip/train_images   
   ln -s PATH_TO_LIP_VAL_IMAGES_DIR dataset/lip/val_images      
   ln -s PATH_TO_LIP_TEST_IMAGES_DIR dataset/lip/testing_images   
   ln -s PATH_TO_LIP_TRAIN_SEGMENTATION_ANNO_DIR dataset/lip/train_segmentations   
   ln -s PATH_TO_LIP_VAL_SEGMENTATION_ANNO_DIR dataset/lip/val_segmentations   
   

Citation

If you use our code/model in your work or find it is helpful, please cite the paper:

@inproceedings{nie2018pil,
  title={Human Pose Estimation with Parsing Induced Learner},
  author={Nie, Xuecheng and Feng, Jiashi and Zuo, Yiming and Yan, Shuicheng},
  booktitle={CVPR},
  year={2018}
}