Go Closer to See Better: Camouflaged Object Detection via Object Area Amplification and Figure-Ground Conversion

paper link: https://ieeexplore.ieee.org/document/10065514

prediction maps and pretrained model

1. The prediction map of our method can be downloaded at https://drive.google.com/drive/folders/1rZ9IrbFz4dggik1vnK53PnNNy7l-1X_r?usp=sharing.
2. The pretrained model of our model can be downloaded at https://drive.google.com/drive/folders/1n80O0RIAe4KT08SZG-UK6HsWgD_qouoQ?usp=sharing.

environment

1. python = Python 3.8.13
2. others packages can be found at requirement.txt

start

git clone https://github.com/Haozhe-Xing/SARNet.git

conda create --name myenv python=3.8.13

conda activate myenv

pip install -r requirements.txt

New: about the features map visualization！

if you want to visualize your features maps like the above imgages, you can user the code in folder "display_heatmpas".

if you want to visualize your model predictions like the above imgages, you can user the code in folder "display_heatmpas/combine.py".