Minglong Li
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Papers from this author
Global-Local Attention Network for Semantic Segmentation in Aerial Images
Minglong Li, Lianlei Shan, Weiqiang Wang
Auto-TLDR; GLANet: Global-Local Attention Network for Semantic Segmentation
Abstract Slides Poster Similar
Errors in semantic segmentation task could be classified into two types: large area misclassification and local inaccurate boundaries. Previously attention based methods capture rich global contextual information, this is beneficial to diminish the first type of error, but local imprecision still exists. In this paper we propose Global-Local Attention Network (GLANet) with a simultaneous consideration of global context and local details. Specifically, our GLANet is composed of two branches namely global attention branch and local attention branch, and three different modules are embedded in the two branches for the purpose of modeling semantic interdependencies in spatial, channel and boundary dimensions respectively. We sum the outputs of the two branches to further improve feature representation, leading to more precise segmentation results. The proposed method achieves very competitive segmentation accuracy on two public aerial image datasets, bringing significant improvements over baseline.