Multiscale UAV small target detection based on multispectral interactive attention fusion
Aiming at the challenges in UAV detection,such as small target size,significant influence by back-ground environment,and difficulties in deep fusion of multispectral features,this paper proposes a multiscale multispectral interactive attention fusion target detection model for small UAV target identification.Firstly,the backbone network is designed as a dual-flow network to extract the infrared and visible features at differ-ent scales,with the addition of small target detection layer and BiFPN cascade operation to enhance the ex-traction capability of UAV small target features.Secondly,an innovative multispectral interactive attention fu-sion module is designed.Under the guidance of this fusion module,the network can fuse the infrared and vis-ible modalities'information at different scales,allowing for deep aggregation of their repective features,lever-aging the strengths of each modality,and guiding the UAV small target detection.The experimental results demonstrate that compared to state-of-the-art multispectral target detection models,the model proposed in this paper achieves superior performance on the two public multispectral target detection datasets,FLIR and LLVIP.Furthmore,on the constructed multispectral UAV dataset,the proposed model effectively improves UAV detection accuracy and robustness of UAV.
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