University of Oulu

Xu Y., Hong X., Zhao G. (2019) Salient Object Detection with CNNs and Multi-scale CRFs. In: Felsberg M., Forssén PE., Sintorn IM., Unger J. (eds) Image Analysis. SCIA 2019. Lecture Notes in Computer Science, vol 11482. Springer, Cham

Salient object detection with CNNs and multi-scale CRFs

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Author: Xu, Yingyue1; Hong, Xiaopeng1; Zhao, Guoying1
Organizations: 1Center for Machine Vision and Signal Analysis, University of Oulu
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
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Language: English
Published: Springer Nature, 2019
Publish Date: 2020-05-12


Recent CNNs based salient object detection approaches tend to embed a fully connected Conditional Random Field (CRF) layer to refine the saliency maps from CNNs for post processing. Due to the significant performance enhancement by the CRF layer, in this paper, we propose a more flexible CRF refinement framework by embedding the CRF inference to multiple levels of side outputs from CNNs for multi-scale saliency refinement. A fully convolutional neural networks based on the simple yet effective encoder-decoder architecture with only three scales of side output maps is pre-trained. Then, the CRF layers are embedded to each scale of the side output respectively to complement the defects of each side output maps. Finally, the refined side output maps are fused and refined by another CRF inference for the final saliency map. The proposed multi-scale CRFs model (MCRF) is trained with low computational costs and shows competitive performance over four datasets in comparison with the existing state-of-the-art saliency models.

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Series: Lecture notes in computer science
ISSN: 0302-9743
ISSN-E: 1611-3349
ISSN-L: 0302-9743
ISBN: 978-3-030-20205-7
ISBN Print: 978-3-030-20204-0
Pages: 233 - 245
DOI: 10.1007/978-3-030-20205-7_20
Host publication: Image analysis : 21st Scandinavian Conference, SCIA 2019, Norrköping, Sweden, June 11–13, 2019, proceedings
Host publication editor: Felsberg, Michael
Forssén, Per-Erik
Sintorn, Ida-Maria
Unger, Jonas
Conference: Scandinavian Conference on Image Analysis
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Copyright information: © Springer Nature Switzerland AG 2019. This is a post-peer-review, pre-copyedit version of an article published in Image analysis : 21st Scandinavian Conference, SCIA 2019, Norrköping, Sweden, June 11–13, 2019, proceedings. The final authenticated version is available online at: