Code repository for our paper entilted "Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection" accepted at TCSVT 2024.
arXiv version: https://arxiv.org/abs/2406.01127.
24.7.19. The prediction results and weights based on VGG and ResNet backbones have been updated in the Baidu network disk link below.
If you think our work is helpful, please cite
@article{wang2024learning,
title={Learning Adaptive Fusion Bank for Multi-modal Salient Object Detection},
author={Wang, Kunpeng and Tu, Zhengzheng and Li, Chenglong and Zhang, Cheng and Luo, Bin},
journal={IEEE Transactions on Circuits and Systems for Video Technology},
year={2024},
publisher={IEEE}
}
RGB-D and RGB-T SOD datasets can be found here. [baidu pan fetch code: chjo]
Saliency maps can be found here. [baidu pan fetch code: uodf]
Pretrained parameters can be found here.[baidu pan fetch code: 3ed6]
- Create directories for the experiment and parameter files.
- Please use
conda
to installtorch
(1.12.0) andtorchvision
(0.13.0). - Install other packages:
pip install -r requirements.txt
. - Set your path of all datasets in
./Code/utils/options.py
.
python train.py
python test_produce_maps.py
If you have any questions, please contact us ([email protected]).