# mkocabas/pose-residual-network

Code for the Pose Residual Network introduced in 'MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network (ECCV 2018)' paper
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# Pose Residual Network

This repository contains a Keras implementation of the Pose Residual Network (PRN) presented in our ECCV 2018 paper:

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

PRN is described in Section 3.2 of the paper.

## Getting Started

We have tested our method on COCO Dataset

### Prerequisites

``````python
tensorflow
keras
numpy
tqdm
pycocotools
progress
scikit-image
``````

### Installing

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

2. Install Tensorflow.

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 main.py`

For more options take a look at `opt.py`

## Results

Results on COCO val2017 Ground Truth data.

`````` Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets= 20 ] = 0.894
Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets= 20 ] = 0.971
Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets= 20 ] = 0.912
Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.875
Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = 0.918
Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 20 ] = 0.909
Average Recall     (AR) @[ IoU=0.50      | area=   all | maxDets= 20 ] = 0.972
Average Recall     (AR) @[ IoU=0.75      | area=   all | maxDets= 20 ] = 0.928
Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets= 20 ] = 0.896
Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets= 20 ] = 0.947
``````

Pytorch Version

## Citation

If you find this code useful for your research, please consider citing our 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}
}
``````
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