porky12 / pose-residual-network-pytorch

Code for the Pose Residual Network introduced in 'MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network' paper https://arxiv.org/abs/1807.04067

Pose Residual Network

This is the code for the paper:

Muhammed Kocabas, Salih Karagoz, Emre Akbas. MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network. In ECCV, 2018. arxiv

This repo includes PRN (pose residual network) module introduced in Section 3.2 of the paper.

Getting Started

We have tested our method on Coco Dataset

Prerequisites

python
pytorch
numpy
tqdm
pycocotools
progress
scikit-image

Installing

1. Clone this repository git clone https://github.com/salihkaragoz/pose-residual-network-pytorch.git

2. Install Pytorch

3. pip install -r src/requirements.txt

4. To download COCO dataset train2017 and val2017 annotations run: bash data/coco.sh. (data size: ~240Mb)

Training

python train.py

For more options look at opt.py

Results

Results on COCO val2017 Ground Truth data.

 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets= 20 ] = 0.880
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets= 20 ] = 0.968
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets= 20 ] = 0.908
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.870
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = 0.898
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 20 ] = 0.904
 Average Recall     (AR) @[ IoU=0.50      | area=   all | maxDets= 20 ] = 0.974
 Average Recall     (AR) @[ IoU=0.75      | area=   all | maxDets= 20 ] = 0.920
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.889
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = 0.931

License

Citation

If you find this code useful for your research, please consider citing the following paper:

@Inproceedings{kocabas18prn,
  Title          = {Multi{P}ose{N}et: Fast Multi-Person Pose Estimation using Pose Residual Network},
  Author         = {Kocabas, Muhammed and Karagoz, Salih and Akbas, Emre},
  Booktitle      = {European Conference on Computer Vision (ECCV)},
  Year           = {2018}
}