This project provides the code and results for 'Adaptive Dual-Stream Sparse Transformer Network for Salient Object Detection in Optical Remote Sensing Images', IEEE J-STARS, 2024 (IEEE Link).
The datasets utilized in this work can be accessed from BaiDuYunlink (code:2r9f), including ORSSD, EORSSD, ORSI-4199 and RSISOD.
We provide saliency maps of our ADSTNet based on Res2Net in BaiDuYunlink (code:ADST) on ORSSD, EORSSD and ORSI-4199.
You can use the evaluation tool (MATLAB version) to evaluate the above saliency maps.
We provide saliency maps of ADSTNet base on the others backbone (VGG and ResNet) in BaiDuYunlink (code:ADST).
We provide saliency maps of some semantic segmentation methods in BaiDuYunlink (code:ADST).
If you find this work interesting and use our dataset in your research, please cite:
@article{zhao2024adaptive,
title={Adaptive Dual-Stream Sparse Transformer Network for Salient Object Detection in Optical Remote Sensing Images},
author={Zhao, Jie and Jia, Yun and Ma, Lin and Yu, Lidan},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
volume={17},
pages={5173--5192},
year={2024},
publisher={IEEE}
}
If you encounter any problems with the code, want to report bugs, etc.
Please contact me at [email protected].