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<!-- PROJECT LOGO --> <br /> <p align="center"> <a href="http://zhaozhang.net/coca.html"> <img src="img/GICD_LOGO.png" alt="Logo" width="210" height="100"> </a> <h3 align="center">Gradient-Induced Co-Saliency Detection</h3> <p align="center"> Zhao Zhang*, Wenda Jin*, Jun Xu, Ming-Ming Cheng <br /> <a href="http://zhaozhang.net/coca.html"><strong>⭐ Project Home »</strong></a> <br /> <!-- <a href="https://arxiv.org/abs/2004.13364" target="_black">[PDF]</a> <a href="#" target="_black">[Code]</a> <a href="https://www.bilibili.com/video/BV1y5411a7Rq/" target="_black">[Short Video]</a> <a href="https://www.bilibili.com/video/BV1bi4y137c6" target="_black">[Long Video]</a> <a href="http://zhaozhang.net/papers/20_GICD/slides.pdf" target="_black">[Slides]</a> <a href="http://zhaozhang.net/papers/20_GICD/translation.pdf" target="_black">[中译版]</a> <a href="./papers/20_GICD/bibtex.txt" target="_black">[bib]</a> <br /> <br /> --> </p> </p> <p align="center"> <a href="https://arxiv.org/abs/2004.13364"> <img src="https://img.shields.io/badge/PDF-%F0%9F%93%83-green" target="_blank" /> </a> <a href="https://www.bilibili.com/video/BV1y5411a7Rq/"> <img alt="Bilibili" src="https://img.shields.io/badge/Short%20Video-%F0%9F%8E%A5-orange" target="_blank" /> </a> <a alt="Bilibili" href="https://www.bilibili.com/video/BV1bi4y137c6"> <img src="https://img.shields.io/badge/Long%20Video-%F0%9F%8E%AC-blue" /> </a> <a href="http://zhaozhang.net/papers/20_GICD/slides.pdf"> <img src="https://img.shields.io/badge/Slides-%F0%9F%97%92-yellow"> </a> <a href="http://zhaozhang.net/papers/20_GICD/translation.pdf"> <img src="https://img.shields.io/badge/%E4%B8%AD%E8%AF%91%E7%89%88-%F0%9F%90%BC-red"> </a> </p>The official repo of the ECCV 2020 paper Gradient-Induced Co-Saliency Detection.
More details can be found at our project home.
Prerequisites
Environments
- PyTorch >= 1.0
- tqdm
Pretrained model
Download gicd_ginet.pth (Baidu (05cl)/Google Drive).
Usage
- Configure the input root and the output root in
test.sh
--param_path ./gicd_ginet.pth (pretrained model path)
--input_root your_data_root (categorize by subfolders)
--save_root your_output_root
- Run by
sh test.sh
Prediction results
The co-saliency maps of GICD can be found at our project home.
Citation
If you find this work is useful for your research, please cite our paper:
@inproceedings{zhang2020gicd,
title={Gradient-Induced Co-Saliency Detection},
author={Zhang, Zhao and Jin, Wenda and Xu, Jun and Cheng, Ming-Ming},
booktitle={European Conference on Computer Vision (ECCV)},
year={2020}
}
Contact
If you have any questions, feel free to contact me via zzhang🥳mail😲nankai😲edu😲cn