VIGOR : Cross-View Image Geo-localization beyond One-to-one Retrieval

This repository provides the dataset and code used in "VIGOR : Cross-View Image Geo-localization beyond One-to-one Retrieval".

@inproceedings{zhu2021vigor,
  title={VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval},
  author={Zhu, Sijie and Yang, Taojiannan and Chen, Chen},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={3640--3649},
  year={2021}
}

Dataset

Please follow the guideline to download and prepare the dataset.

Requirement

- Python >= 3.5, Opencv, Numpy, Matplotlib
- Tensorflow == 1.13.1

Evaluation from npy

Download the same-area models and npy files from the link, unzip (tar -zxvf) it in "./data/". Then run the script:

python evaluate_from_npy.py

Training and evaluating from model

Download the initialization weights from ImageNet, put it in "./data/". Then run the script to train a simple SAFA baseline:

python train_SAFA.py

Run the script to train with our method:

python train_overall.py

Reference

- https://github.com/shiyujiao/cross_view_localization_SAFA
- https://github.com/Jeff-Zilence/Explain_Metric_Learning
- https://github.com/david-husx/crossview_localisation.git