基于语义传播与前/背景感知的图像语义分割网络

doi:10.16451/j.cnki.issn1003-6059.202201007

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Abstract Although image segmentation is widely applied in many fields owing to the assistance of better analysis and understanding of images, the models based on fully convolutional neural networks still engender the problems of resolution reconstruction and contextual information usage in semantic segmentation. Aiming at the problems, a semantic propagation and fore-background aware network for image semantic segmentation is proposed. A joint semantic propagation up-sampling module(JSPU) is proposed to obtain semantic weights by extracting the global and local semantic information from high-level features. Then the semantic information is propagated from high-level features to low-level features for alleviating the semantic gap between them. The resolution reconstruction is achieved through a hierarchical up-sampling structure. In addition, a pyramid fore-background aware module is proposed to extract foreground and background features of different scales through two parallel branches. Multi-scale fore-background aware features are captured by establishing the dependency relationships between the foreground and background features, thereby the contextual representation of foreground features is enhanced. Experiments on semantic segmentation benchmark datasets show that SPAFBA is superior in performance.

Key words： Semantic Segmentation Fully Convolutional Neural Networks Resolution Reconstruction Contextual Information

Received: 12 August 2021

Fund:National Natural Science Foundation of China(No.61672158), Gerenal Program of Natural Science Foundation of Fujian Province(No.2020J01494), Industry-University Coope-ration Project of Fujian Province(No.2018H6010)

Corresponding Authors: CHEN Yuzhong, Ph.D., professor. His research interests include computing intelligence, computer vision and data mining.

About author:: LIU Zhanghui, master, associate professor. His research interests include data mi-ning.
ZHAN Xiaolu, master student. His research interests include computer vision and artificial intelligence.

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Cite this article:

LIU Zhanghui,ZHAN Xiaolu,CHEN Yuzhong. Image Semantic Segmentation Network Based on Semantic Propagation and Fore-Background Aware[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(1): 71-81.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202201007 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2022/V35/I1/71

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