RS 3 Mamba: Visual State Space Model for Remote Sensing Image Semantic Segmentation

Semantic segmentation of remote sensing images is a fundamental task in geoscience research. However, convolutional neural networks (CNNs) and transformers have some significant shortcomings. The former are limited by insufficient long-range modeling capabilities, while the latter are hampered by computational complexity. Recently, a novel visual state space (VSS) model represented by Mamba has emerged, capable of modeling long-range relationships with linear computability. In this research, we propose a novel dual-branch network named remote sensing image semantic segmentation Mamba (RS3Mamba) designed specifically for remote sensing tasks. RS3Mamba uses VSS blocks to construct an auxiliary branch, providing…

• NN
  National Natural Science Foundation of China

  Awards: 42371374, 41801323
• GP
  Guangdong Provincial Key Laboratory of Construction Foundation

  Award: 2022B1212010001