Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (19): 214-219.DOI: 10.3778/j.issn.1002-8331.2006-0238

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Salient Detection Model Based on Channel-Spatial Joint Attention Mechanism


  1. 1.桂林电子科技大学 电子工程与自动化学院,广西 桂林 541000
    2.桂林电子科技大学 信息与通信学院,广西 桂林 541000
  • Online:2021-10-01 Published:2021-09-29


CHEN Weijing, ZHOU Ping, YANG Haiyan, YANG Qing, CHEN Rui   

  1. CHEN Weijing, ZHOU Ping, YANG Haiyan, YANG Qing, CHEN Rui


Concerning the problems that exist in computer vision, such as saliency areas highlight unevenness and unclear edges, which lead to poor saliency robustness. To solve this problem, a saliency detection model based on channel-spatial joint attention mechanism is proposed. Firstly, it improves the channel attention mechanism and adds the pixel probability values pixel by pixel in the feature map, so as to better obtain the correlation of information between the channels. Then, it integrates the spatial attention mechanism in parallel with the basis of the channel attention mechanism, and the saliency areas with prominent object are received by weighting the spatial information of the feature map. In addition, to obtain a more fine-grained saliency map, the two feature maps output by the channel and spatial attention mechanism are weighted fusion, which fed back to the channel-spatial joint attention mechanism. Sufficient experiments on public datasets DUTS-TE and SOD demonstrate that the proposed method outperforms the others from the value of F-measure and mean absolute error.

Key words: salient detection, channel attention mechanism, spatial attention mechanism



关键词: 显著性检测, 通道注意力机制, 空间注意力机制