Hierarchical Human Parsing with Typed Part-Relation Reasoning (CVPR2020)

Introduction

The algorithm is described in the CVPR 2020 paper: Hierarchical Human Parsing with Typed Part-Relation Reasoning.

Environment and installation

This repository is developed under CUDA-10.0 and pytorch-1.2.0 in python3.6. The required packages can be installed by:

pip install -r requirements.txt

Structure of repo

$HierarchicalHumanParsing
├── checkpoints
│   ├── init
├── dataset
│   ├── list
├── doc
├── inplace_abn
│   ├── src
├── modules
├── network
├── utils

Running the code

python evaluate_pascal.py

Citation

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

@InProceedings{Wang_2020_CVPR,
author = {Wang, Wenguan and Zhu, Hailong and Dai, Jifeng and Pang, Yanwei and Shen, Jianbing and Shao, Ling},
title = {Hierarchical Human Parsing With Typed Part-Relation Reasoning},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}

@InProceedings{Wang_2019_ICCV,
author = {Wang, Wenguan and Zhang, Zhijie and Qi, Siyuan and Shen, Jianbing and Pang, Yanwei and Shao, Ling},
title = {Learning Compositional Neural Information Fusion for Human Parsing},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}