当前位置: X-MOL 学术Electron. Lett. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
ABiFN: Attention-based bi-modal fusion network for object detection at night time
Electronics Letters ( IF 0.7 ) Pub Date : 2020-12-01 , DOI: 10.1049/el.2020.1952
A. Sai Charan 1 , M. Jitesh 1 , M. Chowdhury 2 , H. Venkataraman 1
Affiliation  

Camera-based object detection in low-light/night-time conditions is a fundamental problem because of insufficient lighting. So far, a mid-level fusion of RGB and thermal images is done to complement each other's features. In this work, an attention-based bi-modal fusion network is proposed for a better object detection in the thermal domain by integrating a channel-wise attention module. The experimental results show that the proposed framework improves the mAP by 4.13 points on the FLIR dataset.

中文翻译:

ABiFN:用于夜间目标检测的基于注意力的双峰融合网络

由于光线不足,在弱光/夜间条件下基于摄像机的物体检测是一个基本问题。到目前为止,已经完成了RGB和热图像的中间融合,以补充彼此的功能。在这项工作中,提出了一种基于注意力的双峰融合网络,通过集成基于通道的注意力模块,可以更好地在热域中进行物体检测。实验结果表明,所提出的框架将FLIR数据集的mAP提高了4.13点。
更新日期:2020-12-04
down
wechat
bug