Learning Compositional Neural Infomation Fusion for Human Parsing (ICCV19)

Introduction

The algorithm is described in the ICCV 2019 paper: Learning Compositional Neural Infomation Fusion for Human Parsing. In this work, we propose to combine neural networks with the compositional hierarchy of human bodies for efficient and complete human parsing.

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Environment and installation

This repository is developed under CUDA9.0 and pytorch-0.4.1 in python3.6. Early versions of pytorch can be found here. The required packages can be installed by:

pip install -r requirements.txt

Structure of repo

$CompositionalHumanParsing
├── dataset
│   ├── list
├── doc
├── inplace_abn
│   ├── src
├── module
├── network
├── progress

Running the code

1. Download the pre-trained model.

python evaluate.py --root <path to the dataset> --restore_from <path to the pre-traiend model>

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Citation

If you find this code useful, please cite our work with the following bibtex:

@inproceedings{wang2019learning,
  title={Learning compositional neural information fusion for human parsing},
  author={Wang, Wenguan and Zhang, Zhijie and Qi, Siyuan and Shen, Jianbing and Pang, Yanwei and Shao, Ling},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  pages={5703--5713},
  year={2019}
}