Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images

Authors

Ning Zhang, Francesco Nex, Norman Kerle, George Vosselman

Introduction

This repository contains the dataset and source code of our victim detection paper.

Dataset

We provide the harmonized composite victim images generated by our unsupervised harmonization network (train.py). You can use them to fine-tune your own victim detector.

Harmonized composite images: https://surfdrive.surf.nl/files/index.php/s/yPtgoTrB4CohOL0

Fine-tune a yolov5 detector

To fine-tune your yolov5 detector you need to put the configuration file (./yolov5/victimdet.yaml) to your own yolov5 dataset path.

Citation

If you use our code or dataset please cite our papers:

@article{zhang2022training,
title={Training a Disaster Victim Detection Network for UAV Search and Rescue Using Harmonious Composite Images},
author={Zhang, Ning and Nex, Francesco and Vosselman, George and Kerle, Norman},
journal={Remote Sensing},
volume={14},
number={13},
pages={2977},
year={2022},
publisher={Multidisciplinary Digital Publishing Institute}
}


@article{zhang2022unsupervised,
title={Unsupervised harmonious image composition for disaster victim detection},
author={Zhang, Ning and Nex, F and Vosselman, G and Kerle, N},
journal={The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences},
volume={43},
pages={1189--1196},
year={2022},
publisher={Copernicus GmbH}
}