论文标题
polardet：旋转目标的快速，更精确的检测器
PolarDet: A Fast, More Precise Detector for Rotated Target in Aerial Images
论文作者
论文摘要
多年来，高分辨率航空图像的快速，精确的对象检测一直是一项艰巨的任务。由于物体尺度，旋转和纵横比的急剧变化，大多数现有方法效率低下且不精确。在本文中，我们在极坐标中通过极性方法表示定向对象，并提出Polardet，Polardet是基于该表示的快速准确的一阶段对象检测器。我们的检测器引入了子像素中心的语义结构，以进一步改善分类的真实性。 Polardet以更快的推理速度实现了空中对象检测任务中几乎所有SOTA性能。详细介绍，我们的方法分别在DOTA，UCAS-AOD，HRSC上获得76.64 \％MAP，97.01 \％MAP和90.46 \％MAP的SOTA结果。最值得注意的是，我们的polardet获得了最佳性能，并在UCAS-AOD数据集中达到了最快的速度（32fps）。
Fast and precise object detection for high-resolution aerial images has been a challenging task over the years. Due to the sharp variations on object scale, rotation, and aspect ratio, most existing methods are inefficient and imprecise. In this paper, we represent the oriented objects by polar method in polar coordinate and propose PolarDet, a fast and accurate one-stage object detector based on that representation. Our detector introduces a sub-pixel center semantic structure to further improve classifying veracity. PolarDet achieves nearly all SOTA performance in aerial object detection tasks with faster inference speed. In detail, our approach obtains the SOTA results on DOTA, UCAS-AOD, HRSC with 76.64\% mAP, 97.01\% mAP, and 90.46\% mAP respectively. Most noticeably, our PolarDet gets the best performance and reaches the fastest speed(32fps) at the UCAS-AOD dataset.
