Light weight rotating object detector based on angle sensitive spatial attention mechanism

Kaishi YIN; Meng YANG; Xi GU; Zhicheng WANG

doi:10.11959/j.issn.2096-6652.202133

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Light weight rotating object detector based on angle sensitive spatial attention mechanism

Special Issue: Intelligent Object Detection and Recognition | 更新时间：2024-06-05

- Light weight rotating object detector based on angle sensitive spatial attention mechanism
- Chinese Journal of Intelligent Science and Technology Vol. 3, Issue 3, Pages: 322-333(2021)
- 作者机构：
  
  1. 东华大学计算机科学与技术学院，上海 201620
  2. 中国舰船研究设计中心，湖北武汉 430064
  3. 同济大学电子与信息工程学院，上海 201804
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-6652.202133
  CLC： TP181
- Published Online：2021-09，
  
  Published：15 September 2021
- 稿件说明：
移动端阅览
Kaishi YIN, Meng YANG, Xi GU, et al. Light weight rotating object detector based on angle sensitive spatial attention mechanism[J]. Chinese journal of intelligent science and technology, 2021, 3(3): 322-333.
DOI：

Kaishi YIN, Meng YANG, Xi GU, et al. Light weight rotating object detector based on angle sensitive spatial attention mechanism[J]. Chinese journal of intelligent science and technology, 2021, 3(3): 322-333. DOI： 10.11959/j.issn.2096-6652.202133.

摘要

随着深度学习的快速发展，近年来越来越多的基于锚框的目标检测算法被应用于遥感图像上，然而提高算法精度的代价是牺牲了检测速度。因此，选择无锚框的目标检测网络框架，针对遥感场景的特点，提出了一种旋转框的遥感检测算法。根据旋转框与其外接矩形框的空间位置关系，提出了一种简单有效的旋转框表示方式。此外，设计了一种用于辅助检测旋转目标的角度敏感的空间注意力机制，通过引入角度信息提升模型对旋转目标的检测能力。提出的算法在公开遥感数据集DOTA上进行了实验，旋转框的目标检测网络的平均精度均值达到了68.5%，检测速度达到了每秒17.4帧图像。

Abstract

With the rapid development of deep learning

more and more target detection algorithms based on anchor frame are applied to remote sensing images in recent years.However

the cost of improving the accuracy of the algorithm is to sacrifice the detection speed.Therefore

the target detection network framework of anchor free was chosen

and a remote sensing detection algorithm of rotating frame was proposed according to the characteristics of remote sensing scene.A simple and effective representation of rotating frame was proposed according to the spatial position relationship between rotating frame and its external rectangular frame.In addition

an angle sensitive attention mechanism was designed to assist the detection of rotating targets.By introducing angle information

the detection ability of the model for rotating targets was improved.The proposed algorithm was tested on the open remote sensing dataset DOTA.The mean average precision of target detection network of rotating frame is 68.5% and the detection speed is 17.4 frames per second.

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references

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