CoNet

Code repository for our paper entilted "Accurate RGB-D Salient Object Detection via Collaborative Learning" accepted at ECCV 2020 (poster).

Overall

CoNet Code

> Requirment

• pytorch 1.0.0+
• torchvision
• PIL
• numpy

> Usage

1. Clone the repo

git clone https://github.com/jiwei0921/CoNet.git
cd CoNet/

2. Train/Test

• test
  Coming Soon.

• train
  Coming Soon.

> Results

We provide saliency maps (code: zjzq) of our CoNet on 8 datasets (DUT-RGBD, STEREO, NJUD, LFSD, RGBD135, NLPR, SSD, SIP).

• Note: For evaluation, all results are implemented on this ready-to-use toolbox.

> Related RGB-D Saliency Datasets

All common RGB-D Saliency Datasets we collected are shared in ready-to-use manner.

• The web link is here.

If you think this work is helpful, please cite

@InProceedings{Wei_2020_ECCV,       
   author = {Wei {Ji} and Jingjing {Li} and Miao {Zhang} and Yongri {Piao} and Huchuan {Lu}},   
   title = {Accurate RGB-D Salient Object Detection via Collaborative Learning},     
   booktitle = "ECCV",     
   year = {2020}     
}  

• Thanks for related authors to provide the code or results, particularly, Deng-ping Fan, Hao Chen, Chun-biao Zhu, etc.

Contact Us

More details can be found in Github Wei Ji.
If you have any questions, please contact us ( weiji.dlut@gmail.com ).