Awesome
SCanNet
Pytorch codes of Joint Spatio-Temporal Modeling for Semantic Change Detection in Remote Sensing Images [paper]
Checkpoints
For readers to easily evaluate the accuracy, we provide the trained weights.
SECOND:
LandsatSCD:
Landsat-SCD
The land-scd dataset needs to be pre-processed to meet the experimental settings in this paper. More details are provided at /datasets/LandsatSCD/read_me.md
For readers' convenience, we also provide the preprocessed data:
Baidu Netdisk (psswd lscd)
Cite SCanNet
If you find this work useful or interesting, please consider citing the following BibTeX entry.
@article{ding2024joint,
title={Joint Spatio-Temporal Modeling for Semantic Change Detection in Remote Sensing Images},
author={Ding, Lei and Zhang, Jing and Guo, Haitao and Zhang, Kai and Liu, Bing and Bruzzone, Lorenzo},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2024},
volume={62},
pages={1-14},
doi={10.1109/TGRS.2024.3362795}
}
(Note: This repository is under construction, contents are not final.)