PLFRNet : Perceptual Localization and Focus Refinement Network for RGB-D Salient Object Detection

• This paper can be found at (https://doi.org/10.1016/j.eswa.2024.125278)

Requirements

• python 3.8
• pytorch 2.0.1
• Numpy 1.25.1
• torchvision

RGB-D Trained model weights

• Download the following trained model weights PLFRNet(Code:att3) and put them in ./cpts.

RGB-T Trained model weights

• Download the following trained model weights PLFRNet(Code:q1ky) and put them in ./cpts.

RGB-D Saliency maps

• You can download the tested results map at Baidu Pan link PLFRNet(Code:1234)

RGB-T Saliency maps

• You can download the tested results map at Baidu Pan link PLFRNet(Code:1234)

Evaluate

• You can get the assessment tool at this link (https://github.com/zyjwuyan/SOD_Evaluation_Metrics)

Citation

@article{HAN2025125278,
title = {Perceptual localization and focus refinement network for RGB-D salient object detection},
journal = {Expert Systems with Applications},
volume = {259},
pages = {125278},
year = {2025},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2024.125278},
url = {https://www.sciencedirect.com/science/article/pii/S0957417424021456},
author = {Jinyu Han and Mengyin Wang and Weiyi Wu and Xu Jia},
}

Feel free to send e-mails to me ([email protected]).