This project provides the code and results for 'LSNet: Lightweight Spatial Boosting Network for Detecting Salient Objects in RGB-Thermal Images', IEEE TIP, 2023. IEEE link
Python 3.7+, Pytorch 1.5.0+, Cuda 10.2+, TensorboardX 2.1, opencv-python
if If anything goes wrong with the environment, please check requirements.txt for details.
RGB-T baidu,pin: sf9y / Google drive
RGB-D baidu,pin: 7pi5 / Google drive
matlab verison or python version.
RGB-T baidu pin: fxsk / Google drive
RGB-D baidu pin: 6352 / Google drive
PS: we resize the testing data to the size of 224 * 224 for quicky evaluate.
please check our previous works RGB-T and RGB-D.
RGB-T baidu pin: wnoa / Google drive
RGB-D baidu pin: wnoa / Google drive
@ARTICLE{Zhou_2023_LSNet,
author={Zhou, Wujie and Zhu, Yun and Lei, Jingsheng and Yang, Rongwang and Yu, Lu},
journal={IEEE Transactions on Image Processing},
title={LSNet: Lightweight Spatial Boosting Network for Detecting Salient Objects in RGB-Thermal Images},
year={2023},
volume={},
number={},
pages={1-1},
doi={10.1109/TIP.2023.3242775}}
The implement of this project is based on the code of BBS-Net and Knowledge-Distillation-Zoo. About fps/speed test, please refer MobileSal.
Please drop me an email for any problems or discussion: https://wujiezhou.github.io/ (wujiezhou@163.com) or zzzyylink@gmail.com.