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Abstract

Ship detection is a critical and challenging task in aerial images. Due to the special generation method of SAR images, they have unique characteristics. However, different from objects in natural images, ships in SAR images are often distributed with arbitrary orientations and dense distributions. Recently, key points-based anchor-free object detection algorithms have attracted the attention of quite a few researchers. To solve the task of oriented ship detection based on key points, in this paper, we propose an oriented object detection method based on coordinate system projection (CSProjection). In this work, we first detect the key point of the ship, namely, the center point, then establish a coordinate system with the object center point as the base point, and obtain a bounding box of the oriented object through the projection information of the object. Our method can effectively reduce the number of parameters applied to determine the oriented bounding box during training and decrease the network complexity. Experimental results on several SAR ship detection datasets, including SSDD, SRSDD-v1.0 and the optical remote sensing dataset HRSC2016, indicate that our method can compete with state-of-the-art algorithms for oriented ship detection, even those with more complex backbones.