Papers › PolarDet: A Fast, More Precise Detector for Rotated Target in Aerial Images

PolarDet: A Fast, More Precise Detector for Rotated Target in Aerial Images

17 Oct 2020arXiv:2010.08720archive 2025-07-28

Pengbo Zhao, Zhenshen Qu, Yingjia Bu, Wenming Tan, Ye Ren, ShiLiang Pu

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.

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Tasks

ObjectObject DetectionObject Detection In Aerial Imagesobject-detection

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Object Detection In Aerial Images DOTA PolarDet mAP 76.64% #41 of 58 Archive leaderboard report

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