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Code for CVPR 2019 paper. BASNet: Boundary-Aware Salient Object Detection
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__pycache__ basnet May 19, 2019
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model bn6d_2 Sep 4, 2019
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Code for CVPR 2019 paper 'BASNet: Boundary-Aware Salient Object Detection', Xuebin Qin, Zichen Zhang, Chenyang Huang, Chao Gao, Masood Dehghan and Martin Jagersand.

Contact: xuebin[at]ualberta[dot]ca

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

The SSIM loss is adapted from pytorch-ssim.


  1. Clone this repo
git clone
  1. Download the pre-trained model basnet.pth and put it into the dirctory 'saved_models/basnet_bsi/'

  2. Cd to the directory 'BASNet', run the training or inference process by command: python or python respectively.

We also provide the predicted saliency maps for datasets SOD, ECSSD, DUT-OMRON, PASCAL-S, HKU-IS and DUTS-TE.


BASNet architecture

Quantitative Comparison

Quantitative Comparison

Qualitative Comparison

Qualitative Comparison


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}
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