Open AccessEnvironmental ScienceComputer ScienceEngineering

Q. Fang, Zhaokui Wang

2021.12.6PATTERN RECOGNITION

DOI: 10.1016/j.patcog.2022.108786

tlooto Summary

A simple yet effective CMAFF module that can fuse the complementary information of multispectral remote sensing images with joint common- modality and differential-modality attentions is proposed and confirmed through extensive ablation studies.

Abstract

• We propose a simple yet effective CMAFFmodule that can fuse the complementary information of multispectral remote sensing images with joint common-modality and differential-modality attentions. • We confirm the effectiveness of our cross-modality fusion attention module through extensive ablation studies. • We design a new two-stream object detection network YOLOFusion for multispectral remote sensing images and verify its performance.

Citation format

FANG, Q.; WANG, Zhaokui. Cross-modality attentive feature fusion for object detection in multispectral remote sensing imagery [preprint]. arXiv, 2021. arXiv:2112.02991.