266-cross-view-object-geo-localization-in-a-local-region-with-satellite-imagery
Science Score: 26.0%
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Low similarity (3.7%) to scientific vocabulary
Last synced: 10 months ago
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Basic Info
- Host: GitHub
- Owner: SZU-AdvTech-2024
- Default Branch: main
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Created over 1 year ago
· Last pushed over 1 year ago
Metadata Files
Citation
https://github.com/SZU-AdvTech-2024/266-Cross-View-Object-Geo-Localization-in-a-Local-Region-With-Satellite-Imagery/blob/main/
# Train
1. Firstly, download CVOGL and rename it to 'data', i.e., 'data/CVOGL_DroneAerial' and 'data/CVOGL_SVI'.
2. Secondly, download the pretrained Yolov3 model and place it in the 'saved_models' directory, i.e., './saved_models/yolov3.weights'.
3. Thirdly, execute 'scripts/run_train_all.sh', 'scripts/run_train_droneaerial.sh', or 'scripts/run_train_svi.sh' to train the models.
```shell
sh scripts/run_train_all.sh
# sh scripts/run_train_droneaerial.sh
# sh scripts/run_train_svi.sh
```
# Test
```shell
sh run_test_all.sh
# sh run_test_droneaerial.sh
# sh run_test_svi.sh
```
# Citation
```latex
@ARTICLE{sun10001754,
title={Cross-view Object Geo-localization in a Local Region with Satellite Imagery},
author={Yuxi Sun, Yunming Ye, Jian Kang, Ruben Fernandez-Beltran, Shanshan Feng, Xutao Li, Chuyao Luo, Puzhao Zhang, and Antonio Plaza},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2023}
doi={10.1109/TGRS.2023.3307508}
}
```
Owner
- Name: SZU-AdvTech-2024
- Login: SZU-AdvTech-2024
- Kind: organization
- Repositories: 1
- Profile: https://github.com/SZU-AdvTech-2024
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