News

2025.1 our paper has been accepted by IEEE TIP.

2024.2 arxiv paper released.

Dataset

you can find them here.

During development, we referred to the following resources:

MAE - The backbone of SENet is built based on this project. Note that to get good results, you need to use the full pre-trained weights of MAE (including the decoder part). you can get the mae weight here.
BGNet - The training process and implementation are based on this project.

Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
LICM.py		LICM.py
README.md		README.md
UTIls.py		UTIls.py
dataset		dataset
generate_pred.py		generate_pred.py
get_metric.py		get_metric.py
main_train.py		main_train.py
make_dataset.py		make_dataset.py
net.py		net.py
requirements.txt		requirements.txt