MfrNet: A New Multi-Scale Feature Refining Method for Remote Sensing Image Change Captioning

Remote Sensing Image Change Captioning (RSICC) is an emerging multimodal field with promising prospects. This paper introduces a remote sensing image change caption model based on multi-scale and refined features. First, it extracts multi-scale features from dual-temporal images and then feeds them into the JointAtt and Dence Fusion (JADF) module for attention mutual guidance and feature refinement to eliminate noise. Next, the features are input into a transformer-based sentence generator for change statement generation. We conducted experiments on the Levir-CC dataset comparing our approach with existing methods, the results indicate that our MFRNet outperforms state-of-the-art methods in all metrics.