Semantic segmentation network based on global and local multiscale feature fusion

Abstract

Semantic segmentation networks require huge computing resources, and the main reason is that they have too many feature fusions. In this paper, we propose a multi-scale feature fusion network with global and local fusion. The network is a lightweight network with strong competitiveness in speed and model size, and the segmentation accuracy is also improved to a certain extent.