三角学
计算机科学
目标检测
探测器
算法
光学(聚焦)
代表(政治)
编码
人工智能
计算机视觉
对象(语法)
三角函数
数学
模式识别(心理学)
光学
物理
几何学
电信
生物化学
化学
政治
法学
政治学
基因
作者
Rufei Zhang,Yuqing Wang,Sheng Shen,Wei Zhao,Zhiliang Zeng,Nannan Li,Dongjin Li
标识
DOI:10.1109/lgrs.2023.3313884
摘要
Oriented object detection in aerial images is a crucial link in earth observation. As a special parameter in oriented object representation, angle is the key to achieving high-precision detection. However, the widely-used regression-based methods suffer from boundary discontinuity problem due to the periodicity of angle. To address this issue, we proposed a novel angle prediction method called Fixed Step Trigonometric Coder (FSTC). Exploiting the innate periodicity of trigonometric functions, FSTC can encode angles cyclically in a succinct, continuous, and uniform manner. Based on FSTC, we designed a single-shot oriented object detector, namely, Trigonometric-coded Refined Detector (TRDet), for high-precision object detection in real-time. TRDet consists of two modules: the Angle Optimization Module (AOM) and the Object Detection Module (ODM). AOM employs FSTC to generate high-quality rotated anchors. In ODM, a Dynamically Weighted Loss (DWL) was proposed to make the model focus on hard samples with higher angle deviation. Extensive experiments on DOTA and HRSC2016 show that both FSTC and TRDet can achieve competitive performance compared with peer works.
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