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https://github.com/xuebinqin/basnet

Code for CVPR 2019 paper. BASNet: Boundary-Aware Salient Object Detection
https://github.com/xuebinqin/basnet

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Code for CVPR 2019 paper. BASNet: Boundary-Aware Salient Object Detection

Host: GitHub
URL: https://github.com/xuebinqin/basnet
Owner: xuebinqin
License: mit
Created: 2019-03-29T20:53:30.000Z (almost 6 years ago)
Default Branch: master
Last Pushed: 2023-09-10T11:28:16.000Z (over 1 year ago)
Last Synced: 2024-10-29T17:56:06.425Z (2 months ago)
Language: Python
Homepage:
Size: 3.53 MB
Stars: 1,382
Watchers: 35
Forks: 249
Open Issues: 21
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # BASNet (New Version May 2nd, 2021)

'[Boundary-Aware Segmentation Network for

Mobile and Web Applications](https://arxiv.org/pdf/2101.04704.pdf)', Xuebin Qin, Deng-Ping Fan, Chenyang Huang, Cyril Diagne, Zichen Zhang,

Adria Cabeza Sant’Anna, Albert Suarez, Martin Jagersand, and Ling Shao. 

## Salient Object Detection(SOD) Qualitative Comparison

![SOD Qualitative Comparison](figures/sod_qual_comp.PNG)

## Salient Objects in Clutter(SOC) Qualitative Comparison

![SOC Qualitative Comparison](figures/soc_qual_comp.PNG)

## Camouflaged Object Detection(COD) Qualitative Comparison

![COD Qualitative Comparison](figures/cod_qual_comp.PNG)

## Predicted maps of SOD, SOC and COD datasets

[SOD Results will come soon!]() \

[SOC Results will come soon!]() \

[COD Results](https://drive.google.com/file/d/12jijUPpdOe7k2O1YcLbkJHyXCJb3MRMN/view?usp=sharing)

# BASNet (CVPR 2019)

Code for CVPR 2019 paper '[*BASNet: Boundary-Aware Salient Object Detection*](http://openaccess.thecvf.com/content_CVPR_2019/html/Qin_BASNet_Boundary-Aware_Salient_Object_Detection_CVPR_2019_paper.html) [code](https://github.com/NathanUA/BASNet)', [Xuebin Qin](https://webdocs.cs.ualberta.ca/~xuebin/), [Zichen Zhang](https://webdocs.cs.ualberta.ca/~zichen2/), [Chenyang Huang](https://chenyangh.com/), [Chao Gao](https://cgao3.github.io/), [Masood Dehghan](https://sites.google.com/view/masooddehghan) and [Martin Jagersand](https://webdocs.cs.ualberta.ca/~jag/). 

__Contact__: xuebin[at]ualberta[dot]ca

## (2020-May-09) NEWS! Our new Salient Object Detection model (U^2-Net), which is just accepted by Pattern Recognition, is available now!

[U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection](https://github.com/NathanUA/U-2-Net)

## Evaluation

[Evaluation Code](https://github.com/NathanUA/Binary-Segmentation-Evaluation-Tool)

## Required libraries

Python 3.6  

numpy 1.15.2  

scikit-image 0.14.0  

PIL 5.2.0  

PyTorch 0.4.0  

torchvision 0.2.1  

glob  

The SSIM loss is adapted from [pytorch-ssim](https://github.com/Po-Hsun-Su/pytorch-ssim/blob/master/pytorch_ssim/__init__.py).  

## Usage

1. Clone this repo

```

git clone https://github.com/NathanUA/BASNet.git

```

2. Download the pre-trained model basnet.pth from [GoogleDrive](https://drive.google.com/open?id=1s52ek_4YTDRt_EOkx1FS53u-vJa0c4nu) or [baidu](https://pan.baidu.com/s/1PrsBdepwrkMWPLSW22FhAg) extraction code: 6phq, and put it into the dirctory 'saved_models/basnet_bsi/'

3.  Cd to the directory 'BASNet', run the training or inference process by command: ```python basnet_train.py```

or ```python basnet_test.py``` respectively.  

 We also provide the predicted saliency maps ([GoogleDrive](https://drive.google.com/file/d/1K9y9HpupXT0RJ4U4OizJ_Uk5byUyCupK/view?usp=sharing),[Baidu](https://pan.baidu.com/s/1FJKVO_9YrP7Iaz7WT6Xdhg)) for datasets SOD, ECSSD, DUT-OMRON, PASCAL-S, HKU-IS and DUTS-TE.

## Architecture

![BASNet architecture](figures/architecture.png)

## Quantitative Comparison

![Quantitative Comparison](figures/quan.png)

## Qualitative Comparison

![Qualitative Comparison](figures/qual.png)

## Citation

```

@article{DBLP:journals/corr/abs-2101-04704,

  author    = {Xuebin Qin and

               Deng{-}Ping Fan and

               Chenyang Huang and

               Cyril Diagne and

               Zichen Zhang and

               Adri{\`{a}} Cabeza Sant'Anna and

               Albert Su{\`{a}}rez and

               Martin J{\"{a}}gersand and

               Ling Shao},

  title     = {Boundary-Aware Segmentation Network for Mobile and Web Applications},

  journal   = {CoRR},

  volume    = {abs/2101.04704},

  year      = {2021},

  url       = {https://arxiv.org/abs/2101.04704},

  archivePrefix = {arXiv},

}

```

## Citation

```

@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 = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},

month = {June},

year = {2019}

}

```