Evaluation Toolbox for Salient Object Detection

To use this toolbox, read README.md in folder 'tools'.

Datasets [citations]

• ECSSD link
• PASCAL-S link
• DUT-OMRON link
• HKU-IS link
• DUTS link
• SOD link
• SOS link
• THUR link
• MSRA10K link
• SED link

Methods [citations]

Only fully supervised Deep Learning based methods are included.

NOTE: please see my another repo to get the papers.

2019

2018

2017

2016

2015

Table

All saliency maps are provided by the authors or calculated using their released codes.

ECSSD

pre-computed saliency maps [BaiduYun]

pre-computed .mat files [BaiduYun] (please contact me if you need this)

PASCAL-S

pre-computed saliency maps [BaiduYun] Fetch Code: rv6h [Google Drive]

IT'S WEIRD！！！！！THE LINK WILL BE INVALID A FEW DAYS AFTER I UPDATED IT！！！！！

pre-computed .mat files [BaiduYun] (please contact me if you need this)

DUT-OMRON

pre-computed saliency maps [BaiduYun]

pre-computed .mat files [BaiduYun] (please contact me if you need this)

HKU-IS

pre-computed saliency maps [BaiduYun]

pre-computed .mat files [BaiduYun] (please contact me if you need this)

DUTS-test

pre-computed saliency maps [BaiduYun]

pre-computed .mat files [BaiduYun] (please contact me if you need this)

SOD

pre-computed saliency maps [BaiduYun]

pre-computed .mat files [BaiduYun] (please contact me if you need this)

Related Citations (BibTeX)

benchmarks

% ECSSD
@inproceedings{yan2013hierarchical,
  title={Hierarchical saliency detection},
  author={Yan, Qiong and Xu, Li and Shi, Jianping and Jia, Jiaya},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1155--1162},
  year={2013}
}

% PASCAL-S
@inproceedings{li2014secrets,
  title={The secrets of salient object segmentation},
  author={Li, Yin and Hou, Xiaodi and Koch, Christof and Rehg, James M and Yuille, Alan L},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={280--287},
  year={2014}
}

% DUT-OMRON
@inproceedings{yang2013saliency,
  title={Saliency detection via graph-based manifold ranking},
  author={Yang, Chuan and Zhang, Lihe and Lu, Huchuan and Ruan, Xiang and Yang, Ming-Hsuan},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={3166--3173},
  year={2013}
}

% HKU-IS
@inproceedings{li2015visual,
  title={Visual saliency based on multiscale deep features},
  author={Li, Guanbin and Yu, Yizhou},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={5455--5463},
  year={2015}
}

% DUTS
@inproceedings{wang2017,
  title={Learning to Detect Salient Objects with Image-level Supervision},
  author={Wang, Lijun and Lu, Huchuan and Wang, Yifan and Feng, Mengyang and Wang, Dong, and Yin, Baocai and Ruan, Xiang}, 
  booktitle={CVPR},
  year={2017}
}

% SOD
@inproceedings{movahedi2010design,
  title={Design and perceptual validation of performance measures for salient object segmentation},
  author={Movahedi, Vida and Elder, James H},
  booktitle={Computer Vision and Pattern Recognition Workshops (CVPRW), 2010 IEEE Computer Society Conference on},
  pages={49--56},
  year={2010},
  organization={IEEE}
}

% SOS
@inproceedings{zhang2015salient,
  title={Salient object subitizing},
  author={Zhang, Jianming and Ma, Shugao and Sameki, Mehrnoosh and Sclaroff, Stan and Betke, Margrit and Lin, Zhe and Shen, Xiaohui and Price, Brian and Mech, Radomir},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={4045--4054},
  year={2015}
}

% THUR
@article{cheng2014salientshape,
  title={Salientshape: Group saliency in image collections},
  author={Cheng, Ming-Ming and Mitra, Niloy J and Huang, Xiaolei and Hu, Shi-Min},
  journal={The Visual Computer},
  volume={30},
  number={4},
  pages={443--453},
  year={2014},
  publisher={Springer}
}

% MSRA10K
@article{ChengPAMI,
  author = {Ming-Ming Cheng and Niloy J. Mitra and Xiaolei Huang and Philip H. S. Torr and Shi-Min Hu},
  title = {Global Contrast based Salient Region Detection},
  year  = {2015},
  journal= {IEEE TPAMI},
  volume={37}, 
  number={3}, 
  pages={569--582}, 
  doi = {10.1109/TPAMI.2014.2345401},
}

% SED
@inproceedings{alpert2007image,
  title={Image segmentation by probabilistic bottom-up aggregation and cue integration},
  author={Alpert, Sharon and Galun, Meirav and Basri, Ronen and Brandt, Achi},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1--8},
  year={2007},
  organization={IEEE}
}

algorithms

%MLMSNet
@InProceedings{WuRunMin_2019_CVPR,
   author = {Wu, Runmin and Feng, Mengyang and Guan, Wenlong and Wang, Dong and Lu, Huchuan and Ding, Errui},
   title = {A Mutual Learning Method for Salient Object Detection with intertwined Multi-Supervision},
   booktitle = CVPR,
   year = {2019}
}

%CPD
@InProceedings{Wu_2019_CVPR,
   author = {Wu, Zhe and Su, Li and Huang, Qingming},
   title = {Cascaded Partial Decoder for Fast and Accurate Salient Object Detection},
   booktitle = CVPR,
   year = {2019}
}

%BASNet
@InProceedings{Qin_2019_CVPR,
   author = {Qin, Xuebin and Zhang, Zichen and Huang, Chenyang and Gao, Chao and Dehghan, Masood and Jagersand, Martin},
   title = {BASNet: Boundary-Aware Salient Object Detection},
   booktitle = CVPR,
   year = {2019}
}

%PoolNet
@inproceedings{Liu2019PoolSal,
   title={A Simple Pooling-Based Design for Real-Time Salient Object   Detection},
   author={Liu, Jiang-Jiang and Hou, Qibin and Cheng, Ming-Ming and Feng, Jiashi and Jiang, Jianmin},
   booktitle = CVPR,
   year = {2019},
}

%AFNet
@InProceedings{Feng_2019_CVPR,
   author = {Feng, Mengyang and Lu, Huchuan and Ding, Errui},
   title = {Attentive Feedback Network for Boundary-aware Salient Object Detection},
   booktitle = CVPR,
   year = {2019}
}

% BMPM
@inproceedings{zhang2018bi,
  title={A Bi-Directional Message Passing Model for Salient Object Detection},
  author={Zhang, Lu and Dai, Ju and Lu, Huchuan and He, You and Wang, Gang},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1741--1750},
  year={2018}
}

% DGRL
@inproceedings{wang2018detect,
  title={Detect Globally, Refine Locally: A Novel Approach to Saliency Detection},
  author={Wang, Tiantian and Zhang, Lihe and Wang, Shuo and Lu, Huchuan and Yang, Gang and Ruan, Xiang and Borji, Ali},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3127--3135},
  year={2018}
}

% PAGR
@inproceedings{zhang2018progressive,
  title={Progressive Attention Guided Recurrent Network for Salient Object Detection},
  author={Zhang, Xiaoning and Wang, Tiantian and Qi, Jinqing and Lu, Huchuan and Wang, Gang},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={714--722},
  year={2018}
}

% RAS
@inproceedings{chen2018eccv, 
  author={Chen, Shuhan and Tan, Xiuli and Wang, Ben and Hu, Xuelong}, 
  booktitle={European Conference on Computer Vision}, 
  title={Reverse Attention for Salient Object Detection}, 
  year={2018}
} 

% PiCANet
@inproceedings{liu2018picanet,
  title={PiCANet: Learning Pixel-wise Contextual Attention for Saliency Detection},
  author={Liu, Nian and Han, Junwei and Yang, Ming-Hsuan},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3089--3098},
  year={2018}
}

% R3Net
@inproceedings{deng18r,
  author = {Deng, Zijun and Hu, Xiaowei and Zhu, Lei and Xu, Xuemiao and Qin, Jing and Han, Guoqiang and Heng, Pheng-Ann},
  title = {R$^{3}${N}et: Recurrent Residual Refinement Network for Saliency Detection},
  booktitle = {IJCAI},
  year = {2018}
}

% Amulet
@inproceedings{zhang2017amulet,
  title={Amulet: Aggregating multi-level convolutional features for salient object detection},
  author={Zhang, Pingping and Wang, Dong and Lu, Huchuan and Wang, Hongyu and Ruan, Xiang},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  pages={202--211},
  year={2017}
}

% UCF
@inproceedings{zhang2017learning,
  title={Learning uncertain convolutional features for accurate saliency detection},
  author={Zhang, Pingping and Wang, Dong and Lu, Huchuan and Wang, Hongyu and Yin, Baocai},
  booktitle={Computer Vision (ICCV), 2017 IEEE International Conference on},
  pages={212--221},
  year={2017},
  organization={IEEE}
}

% SRM
@inproceedings{wang2017stagewise,
  title={A stagewise refinement model for detecting salient objects in images},
  author={Wang, Tiantian and Borji, Ali and Zhang, Lihe and Zhang, Pingping and Lu, Huchuan},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision},
  pages={4019--4028},
  year={2017}
}

% MSRNet
@inproceedings{li2017instance,
  title={Instance-level salient object segmentation},
  author={Li, Guanbin and Xie, Yuan and Lin, Liang and Yu, Yizhou},
  booktitle={Computer Vision and Pattern Recognition (CVPR), 2017 IEEE Conference on},
  pages={247--256},
  year={2017},
  organization={IEEE}
}

% NLDF
@inproceedings{luo2017non,
  title={Non-local Deep Features for Salient Object Detection.},
  author={Luo, Zhiming and Mishra, Akshaya Kumar and Achkar, Andrew and Eichel, Justin A and Li, Shaozi and Jodoin, Pierre-Marc},
  booktitle={CVPR},
  volume={2},
  number={6},
  pages={7},
  year={2017}
}

% DSS
@inproceedings{hou2017deeply,
  title={Deeply supervised salient object detection with short connections},
  author={Hou, Qibin and Cheng, Ming-Ming and Hu, Xiaowei and Borji, Ali and Tu, Zhuowen and Torr, Philip},
  booktitle={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages={5300--5309},
  year={2017},
  organization={IEEE}
}

% RFCN
@inproceedings{wang2016saliency,
  title={Saliency detection with recurrent fully convolutional networks},
  author={Wang, Linzhao and Wang, Lijun and Lu, Huchuan and Zhang, Pingping and Ruan, Xiang},
  booktitle={European Conference on Computer Vision},
  pages={825--841},
  year={2016},
  organization={Springer}
}

% SCSD-HS
@inproceedings{kim2016shape,
  title={A shape preserving approach for salient object detection using convolutional neural networks},
  author={Kim, Jongpil and Pavlovic, Vladimir},
  booktitle={Pattern Recognition (ICPR), 2016 23rd International Conference on},
  pages={609--614},
  year={2016},
  organization={IEEE}
}

% DS
@article{li2016deepsaliency,
  title={Deepsaliency: Multi-task deep neural network model for salient object detection},
  author={Li, Xi and Zhao, Liming and Wei, Lina and Yang, Ming-Hsuan and Wu, Fei and Zhuang, Yueting and Ling, Haibin and Wang, Jingdong},
  journal={IEEE Transactions on Image Processing},
  volume={25},
  number={8},
  pages={3919--3930},
  year={2016},
  publisher={IEEE}
}

% ELD
@inproceedings{lee2016deep,
  title={Deep saliency with encoded low level distance map and high level features},
  author={Lee, Gayoung and Tai, Yu-Wing and Kim, Junmo},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={660--668},
  year={2016}
}

% DCL
@inproceedings{li2016deep,
  title={Deep contrast learning for salient object detection},
  author={Li, Guanbin and Yu, Yizhou},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={478--487},
  year={2016}
}

% DHSNet
@inproceedings{liu2016dhsnet,
  title={Dhsnet: Deep hierarchical saliency network for salient object detection},
  author={Liu, Nian and Han, Junwei},
  booktitle={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages={678--686},
  year={2016},
  organization={IEEE}
}

% LEGS
@inproceedings{wang2015deep,
  title={Deep networks for saliency detection via local estimation and global search},
  author={Wang, Lijun and Lu, Huchuan and Ruan, Xiang and Yang, Ming-Hsuan},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={3183--3192},
  year={2015}
}

% MCDL
@inproceedings{zhao2015saliency,
  title={Saliency detection by multi-context deep learning},
  author={Zhao, Rui and Ouyang, Wanli and Li, Hongsheng and Wang, Xiaogang},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1265--1274},
  year={2015}
}

% MDF
@inproceedings{li2015visual,
  title={Visual saliency based on multiscale deep features},
  author={Li, Guanbin and Yu, Yizhou},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={5455--5463},
  year={2015}
}

TODO

• [x] add scores in Table
• [x] add pre-computed saliency maps
• [x] add pre-computed .mat files
• [x] add evaluation codes

Cite This Repo

If you find this code useful in your research, please consider citing:

@article{sal_eval_toolbox,
    Author = {Mengyang Feng},
    Title = {Evaluation Toolbox for Salient Object Detection.},
    Journal = {https://github.com/ArcherFMY/sal_eval_toolbox},
    Year = {2018}
}