CATNet: A Cascaded and Aggregated Transformer Network For RGB-D Salient Object Detection

Requirements

python 3.9

pytorch 1.11.0

tensorboardX 2.5

Results and Saliency maps

We provide saliency maps of our CATNet on 7 datasets.

Training

Please run

CatNet_train.py

Pre-trained model and testing

• Download the following pre-trained models (Swin Transformer) and put them in /pre.
• Modify pathes of pre-trained models and datasets.
• Run

CatNet_test.py

Downloading Training and Testing Datasets:

• Download the training set used for training.
• Download the testing sets used for testing.

Citation

If you find this work is useful for your research, please cite our paper:

@article{10179145,
  author={Sun, Fuming and Ren, Peng and Yin, Bowen and Wang, Fasheng and Li, Haojie},
  journal={IEEE Transactions on Multimedia}, 
  title={CATNet: A Cascaded and Aggregated Transformer Network For RGB-D Salient Object Detection}, 
  year={2023},
  volume={},
  number={},
  pages={1-14},
  doi={10.1109/TMM.2023.3294003}}

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