Cross-modality attentive feature fusion for object detection in multispectral remote sensing imagery

作者：

Highlights：

• We propose 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.

• 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.

摘要

•We propose 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.•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.

论文关键词：Cross-modality,Attention,Feature fusion,Object detection,Multispectral remote sensing imagery

论文评审过程：Received 28 September 2021, Revised 28 April 2022, Accepted 7 May 2022, Available online 10 May 2022, Version of Record 20 May 2022.

论文官网地址：https://doi.org/10.1016/j.patcog.2022.108786