LGTC: Local–Global Tri-Consistency Network

Here, we provide the pytorch implementation of the paper: LGTC: Local–Global Tri-Consistency Network for Semi-Supervised Change Detection of Remote Sensing Images.

For more information, please see our published paper at TGRS.

Installation

Clone this repo:

git clone https://github.com/sherryxu21/LGTC.git
cd LGTC

Train

python train.py

Evaluate

python inference.py

Data structure

├─A
├─B
├─label
└─list
  └─5_train_unsupervised.txt
  └─5_train_supervised.txt
  └─val.txt
  └─test.txt

Citation

If you use this code for your research, please cite our paper:

@ARTICLE{11196991,
  author={Liu, Jiamin and Xu, Rui and Luo, Fulin and Fu, Chuan and Guo, Tan and Shi, Qian and Du, Bo},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={LGTC: Local–Global Tri-Consistency Network for Semi-Supervised Change Detection of Remote Sensing Images}, 
  year={2025},
  volume={63},
  number={},
  pages={1-13},
  keywords={Feature extraction;Remote sensing;Semantics;Transformers;Perturbation methods;Robustness;Image reconstruction;Data models;Convolutional neural networks;Context modeling;Change detection (CD);remote sensing (RS);semi-supervised learning (SSL);tri-consistency learning (TCL)},
  doi={10.1109/TGRS.2025.3619036}}

License

Code is released for non-commercial and research purposes only. For commercial purposes, please contact the authors.

Acknowledgements

Appreciate the work from the following repository: FPA-SSCD.