Multi-interactive-Dual-decoder-for-RGBT-Salient-Object-Detection

The pytorch implementation of Multi-interactive Dual-decoder for RGBT Salient Object Detection

Train

We use VT5000-Train to train our network. All the datasets are available in https://github.com/lz118/RGBT-Salient-Object-Detection
The pretrained model (VGG16) can be downloaded at https://pan.baidu.com/s/11lq3mUGRFP7TFvH9Eui14A [3513]

For RGB-T SOD, we provide the our saliency maps on VT821, VT1000 and VT5000-Test.

https://pan.baidu.com/s/1hEZJyEJ2j1n1JKUgUaZZLQ [0div]
The saliency maps of all compared methods on VT821, VT1000 and VT5000-Test. https://pan.baidu.com/s/1s_pJ5qNJcQ8Q7ucusZHnRg [ax96]
For RGB-D SOD, we provide the our saliency maps on SIP, SSD，STERE，LFSD and DES.

https://pan.baidu.com/s/1ZHxvMh818RxlZGW1hQA70w [2oqx]
The evalution toolbox is provided by https://github.com/jiwei0921/Saliency-Evaluation-Toolbox

Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
fig		fig
lib		lib
lib_rgbd		lib_rgbd
Multi-Interactive_Dual-Decoder_for_RGB-Thermal_Salient_Object_Detection.pdf		Multi-Interactive_Dual-Decoder_for_RGB-Thermal_Salient_Object_Detection.pdf
README.md		README.md
net.py		net.py
net_resnet50.py		net_resnet50.py
net_resnet50_4.py		net_resnet50_4.py
smooth_loss.py		smooth_loss.py
test.py		test.py
train.py		train.py
train_resnet50.py		train_resnet50.py
train_resnet50_4.py		train_resnet50_4.py
vgg.py		vgg.py