Yuxuan Li, Danfeng Hong, Chenyu Li, Jing Yao, Jocelyn Chanussot

The code in this toolbox implements the "HD-Net: High-Resolution Decoupled Network for Building Footprint Extraction via Deeply Supervised Body and Boundary Decomposition".

The motivation of image-level and feature-level decoupling in building footprint extraction.

The architecture of the proposed HD-Net.

Please kindly cite the papers if this code is useful and helpful for your research.

Yuxuan Li, Danfeng Hong, Chenyu Li, Jing Yao, Jocelyn Chanussot. HD-Net: High-Resolution Decoupled Network for Building Footprint Extraction via Deeply Supervised Body and Boundary Decomposition. ISPRS Journal of Photogrammetry and Remote Sensing, 2024, 209: 51-65.

 @article{li2024HD,
 title={HD-Net: High-Resolution Decoupled Network for Building Footprint Extraction via Deeply Supervised Body and Boundary Decomposition},
 author={Li, Yuxuan and Hong, Danfeng and Li, Chenyu and Yao, Jing and Chanussote, Jocelyn},
 journal={ISPRS Journal of Photogrammetry and Remote Sensing},
 volume={209},
 pages={51-65},
 year={2024}
 }

Please refer to the file requirements.txt for the running environment of this code.

❗ The pretrained model and datasets can be downloaded from here with key y2a0 or here.

❗ The investigated three building datasets can be accessed from Massachusetts, WHU, Inria.

Copyright (C) 2024 Danfeng Hong

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 of the License.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program.

Danfeng Hong: [email protected]
Danfeng Hong is with the Aerospace Information Research Institute, Chinese Academy of Sciences, 100094 Beijing, China.