Deeply Supervised Salient Object Detection with Short Connections

Qibin Hou1 Ming-Ming Cheng1  Xiaowei Hu1  Ali Borji Zhuowen TuPhilip H. S. Torr4

1CCCE, Nankai University      2CRCV, UCF     3UCSD     4The University of Oxford


Recent progress on saliency detection is substantial, benefiting mostly from the explosive development of Convolutional Neural Networks (CNNs). Semantic segmentation and saliency detection algorithms developed lately have been mostly based on Fully Convolutional Neural Networks (FCNs). There is still a large room for improvement over the generic FCN models that do not explicitly deal with the scale-space problem. Holistically-Nested Edge Detector (HED) provides a skip-layer structure with deep supervision for edge and boundary detection, but the performance gain of HED on saliency detection is not obvious. In this paper, we propose a new saliency method by introducing short connections to the skip-layer structures within the HED architecture. Our framework provides rich multi-scale feature maps at each layer, a property that is critically needed to perform segment detection. Our method produces state-of-the-art results on 5 widely tested salient object detection benchmarks, with advantages in terms of efficiency (0.08 seconds per image), effectiveness, and simplicity over the existing algorithms.


  • Deeply supervised salient object detection with short connections, Qibin Hou, Ming-Ming Cheng, Xiaowei Hu, Zhuowen Tu, Ali Borji, IEEE CVPR, 2017. [pdf] [Project Page] [bib] [source code]

Source Code

You can find our code here. We have uploaded the caffe and CRF packages we used in our paper.

If you find our work is helpful, please cite

  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={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},


andrewhoux AT gmail DOT com


This algorithm is used in flaghship products such as Huawei Mate 10, Hawei Honour V10 etc, to create smart bokeh effects for perfect portraits. See the corresponding


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