BiconNet: An edge-preserved connectivity-based approach for salient object detection
作者：
Highlights：
• A new connectivity-based CNN (BiconNet) for salient object detection is proposed.
• Inter-pixel relationship is modeled by using connectivity masks as training labels.
• Edge features are emphasized via a newly proposed and efficient module.
• BiconNet can be plugged into existing models with a neglectable parameter increase.
• BiconNet outperformed existing salient object detection methods.
摘要
•A new connectivity-based CNN (BiconNet) for salient object detection is proposed.•Inter-pixel relationship is modeled by using connectivity masks as training labels.•Edge features are emphasized via a newly proposed and efficient module.•BiconNet can be plugged into existing models with a neglectable parameter increase.•BiconNet outperformed existing salient object detection methods.
论文关键词：Salient object detection,Visual saliency,Connectivity modeling,Deep learning,Edge modeling
论文评审过程：Received 31 March 2021, Revised 30 June 2021, Accepted 6 August 2021, Available online 13 August 2021, Version of Record 19 August 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.108231
