TNet_TMM2022

Runmin Cong, Kepu Zhang, Chen Zhang, Feng Zheng, Yao Zhao, Qingming Huang, and Sam Kwong, Does Thermal really always matter for RGB-T salient object detection?, IEEE Transactions on Multimedia, 2022. In Press.

Results of TNet:

• Results:
  • We provide the resutls of our TNet on VT5000, VT1000, VT821 datasets.

Baidu Cloud: https://pan.baidu.com/s/1GpTSBtsZHvBjqcDx_8dKyw   Password: 7dab 

Pytorch Code of TNet:

• Pytorch implementation of TNet
• Pretrained model:
  • We provide our testing code. If you test our model, please download the pretrained model, unzip it, and put the TNet.pth to the_model/ folder.
  • Pretrained model download:

Baidu Cloud: https://pan.baidu.com/s/1lrEg-uHPt5Lb2PVEqN4lfQ   Password: iqbe 

Requirements

• Python 3.7
• Pytorch 1.6.0
• torchvision

Data Preprocessing

• Please download the test data, unzip it, and put the VT821, VT1000, VT5000 to Dataset/ folder.
• train and test datasets:

Baidu Cloud: https://pan.baidu.com/s/1mpMKWf-fiN-oqQTepfoDzA   Password: nb9w

Test

python test.py

• You can find the results in the 'Results/' folder.

If you use our TNet, please cite our paper:

@article{TNet,
 title={Does Thermal Really Always Matter for {RGB-T} Salient Object Detection?},
 author={Cong, Runmin and Zhang, Kepu and Zhang, Chen and Zheng, Feng and Zhao, Yao and Huang, Qingming and Kwong, Sam },
 journal={IEEE Transactions on Multimedia},
 year={early access, doi: 10.1109/TMM.2022.3216476},
}

Contact Us:

If you have any questions, please contact Runmin Cong (rmcong@bjtu.edu.cn).