Daff-Net: Dual Attention Feature Fusion Network for Aircraft Detection in Remote Sensing Images

Abstract

Aircraft detection in remote sensing images has always been a research hotspot which has great significance in both civil and military applications. Due to the variations of aircraft types, poses, sizes and complex backgrounds, it is still difficult to effectively and accurately detect aircrafts in remote sensing images. This paper proposes DAFF-Net (Dual Attention Feature Fusion Network), which makes full use of the semantic information of the high-level feature map and the location information of the shallow feature map, and integrates the local features with its global dependency adaptively. Experiments on RSOD aircraft dataset have been implemented, and the results have proved that the detection accuracy of aircraft objects with different scales and densities can all be improved.