https://github.com/zihaomu/gait_recognition_baseline_for_hid2020

The baseline code for the HID 2020 competition
https://github.com/zihaomu/gait_recognition_baseline_for_hid2020

Last synced: 18 days ago
JSON representation

The baseline code for the HID 2020 competition

• Host: GitHub
• URL: https://github.com/zihaomu/gait_recognition_baseline_for_hid2020
• Owner: zihaomu
• License: apache-2.0
• Created: 2020-08-26T01:51:44.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-11-27T00:39:10.000Z (about 4 years ago)
• Last Synced: 2024-12-03T10:51:54.091Z (about 1 month ago)
• Language: Python
• Size: 391 KB
• Stars: 35
• Watchers: 4
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Code example for Human Identification at a Distance 2020 (HID2020)

![overview](./images/overview.png)

## Overview

This code example is made for [HID2020 Competition](http://hid2020.iapr-tc4.org/). The goal of the competition is to provide an evaluation for state-of-the-arts on human identification at a distance (HID). The competition and workshop is endorsed by [IAPR Technical Committee on Biometrics (TC4)](http://iapr-tc4.org/). The workshop will be hosted in conjunction with the Asian Conference on Computer Vision [(ACCV 2020)](http://accv2020.kyoto/) from Nov 30 – Dec 4, 2020.

### How to train you own recognition model?

1. Set you own model struture in ```models/model.py``` and ```models/model_factor.py```.

2. Configure model training config, the default config file is ```./config/baseline_config.yml```.

3. Run code:

```bash

bash train.sh

```

### How to test and generate a submission.csv?

Configure the model used for the test and the path of ```SampleSubmission.csv``` file. 

Run code :

```bash

bash test.sh

```

```./config/baseline_config.yml``` can achieve about 20% accuracy. 

And the output file is ```submission.csv```. **BEFORE** you submit it to [CodaLab](https://competitions.codalab.org/competitions/26085), make sure you compress it into a zip file.

# Citation

The code model refers to the following article. Please cite this paper in your publications if it helps your research:

> @article{zhang2019comprehensive,

> title={A comprehensive study on gait biometrics using a joint CNN-based method},

>  author={Zhang, Yuqi and Huang, Yongzhen and Wang, Liang and Yu, Shiqi},

>  journal={Pattern Recognition},

>  volume={93},

>  pages={228--236},

>  year={2019},

>  publisher={Elsevier}

> }