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Foreground-Aware Relation Network for Geospatial Object ...
Foreground-Aware Relation Network for Geospatial Object Segmentation inHigh Spatial Resolution remote sensing ImageryZhuo Zheng Yanfei Zhong Junjue WangAilong MaWuhan University, Wuhan, China{zhengzhuo, zhongyanfei, kingdrone, Object segmentation, as a particular se-mantic segmentation task, always faces with larger-scalevariation, larger intra-class variance of background, andforeground-background imbalance in the high spatial res-olution (HSR) remote sensing imagery. However, generalsemantic segmentation methods mainly focus on scale vari-ation in the natural scene, with inadequate considerationof the other two problems that usually happen in the largearea earth observation scene. In this paper, we argue thatthe problems lie on the lack of foreground modeling andpropose a Foreground-Aware Relation Network (FarSeg) fromthe perspectives of Relation -based and optimization-basedforeground modeling, to alleviate the above two perspective of Relation , FarSeg enhances the discrim-ination of foreground features via foreground-correlatedcontexts associated by learning foreground-scene , from perspective of optimization.}
remote sensing images that can finely describe various geospatial objects, such as ship, vehicle and airplane, etc. Automatically extracting objects of interest from HSR re-mote sensing imagery is very helpful for urban manage-∗Corresponding author. This work was supported by National Key Research and Development Program of China under Grant No.
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