/AESINet-TGRS

The related files of a paper published on IEEE TGRS.

Primary LanguagePython

AESINet-TGRS

This is a repository for the paper "Adaptive Edge-aware Semantic Interaction Network for Salient Object Detection in Optical Remote Sensing Images", accepted by IEEE TGRS 2023.

Please use the information below to cite our work, thank you.

@ARTICLE{10198281, author={Zeng, Xiangyu and Xu, Mingzhu and Hu, Yijun and Tang, Haoyu and Hu, Yupeng and Nie, Liqiang}, journal={IEEE Transactions on Geoscience and Remote Sensing}, title={Adaptive Edge-Aware Semantic Interaction Network for Salient Object Detection in Optical Remote Sensing Images}, year={2023}, volume={61}, number={}, pages={1-16}, doi={10.1109/TGRS.2023.3300317}}

Model.pth

AESINet-V: https://pan.baidu.com/s/1Xo97lQF4TS2jak9v8iU8jA?pwd=qegm

AESINet-R: https://pan.baidu.com/s/1gYW9qOjR0YjU5R4dCN9Hfg?pwd=tj25

Pretrained(VGG&ResNet): https://pan.baidu.com/s/18k9e3YcxK1rTY8A_WajTyg?pwd=lb8l

Train&Test

Please download the pre-trained model and dataset first, put them under the path of the model, and change the corresponding path in the code. Then use generateTrainList.py and generateTestList.py to generate the path lists of the training set and the test set. Change the dataset path in the code to the path of the dataset listing file (.txt) you specified.

Note

Currently, both ResNet and VGG versions of AESINet codes have been uploaded.

There is still room for improvement in the readability of the code, and the author will update the version with better readability as soon as possible.

If you have any questions, please send an email to: z15264367990@163.com