Bottom-up Human Pose Estimation

Introduction

This is the official code of Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation. This paper has been accepted to CVPR2021.

This repo is built on Bottom-up-Higher-HRNet.

Main Results

Results on COCO val2017 without multi-scale test

Results on COCO val2017 with multi-scale test

Results on COCO test-dev2017 without multi-scale test

Results on COCO test-dev2017 with multi-scale test

Results on CrowdPose test

'*' indicates multi-scale test

Installation

The details about preparing the environment and datasets can be referred to README.md.

Downlaod our pretrained weights from BaidunYun(Password: 8weh) or GoogleDrive to ./models.

Training and Testing

Testing on COCO val2017 dataset using pretrained weights

For single-scale testing:

python tools/dist_valid.py \
    --cfg experiments/coco/higher_hrnet/w32_512_adam_lr1e-3.yaml \
    TEST.MODEL_FILE models/pose_coco/pose_higher_hrnet_w32_512.pth

By default, we use horizontal flip. To test without flip:

python tools/dist_valid.py \
    --cfg experiments/coco/higher_hrnet/w32_512_adam_lr1e-3.yaml \
    TEST.MODEL_FILE models/pose_coco/pose_higher_hrnet_w32_512.pth \
    TEST.FLIP_TEST False

Multi-scale testing is also supported, although we do not report results in our paper:

python tools/dist_valid.py \
    --cfg experiments/coco/higher_hrnet/w32_512_adam_lr1e-3.yaml \
    TEST.MODEL_FILE models/pose_coco/pose_higher_hrnet_w32_512.pth \
    TEST.SCALE_FACTOR '[0.5, 1.0, 2.0]'

Training on COCO train2017 dataset

python tools/dist_train.py \
    --cfg experiments/coco/higher_hrnet/w32_512_adam_lr1e-3.yaml 

By default, it will use all available GPUs on the machine for training. To specify GPUs, use

CUDA_VISIBLE_DEVICES=0,1 python tools/dist_train.py \
    --cfg experiments/coco/higher_hrnet/w32_512_adam_lr1e-3.yaml 

Testing on your own images

python tools/dist_inference.py \
    --img_dir path/to/your/directory/of/images \
    --save_dir path/where/results/are/saved \
    --cfg experiments/coco/higher_hrnet/w32_512_adam_lr1e-3.yaml \
    TEST.MODEL_FILE models/pose_coco/pose_higher_hrnet_w32_512.pth \
    TEST.SCALE_FACTOR '[0.5, 1.0, 2.0]'

Citation

If you find this work or code is helpful in your research, please cite:

@inproceedings{LuoSWAHR,
  title={Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation},
  author={Zhengxiong Luo and Zhicheng Wang and Yan Huang and Liang Wang and Tieniu Tan and Erjin Zhou},
  booktitle={CVPR},
  year={2021}
}