Ship Landmark: An Informative Ship Image Annotation and Its Applications

Visual perception of ships has been attracting increasing attention in the fields of computer vision and ocean engineering. Despite the extensive work related to landmark detection of common objects, the role of landmarks in ship perception has been overlooked. In this paper, we aim to fill this gap by focusing on ship landmarks. Specifically, we give a comprehensive analysis of both the physical structure and deep features of ships, which finds that highlighted areas in feature maps correspond with structurally significant parts of ships. By summarizing the locations of such areas in ships, we define 20 ship landmarks and build the Ship Landmark Dataset (SLAD), the first ship dataset with landmark annotations. We also provide a benchmark for ship landmark detection by evaluating state-of-the-art landmark detection methods on the newly built SLAD. Moreover, we showcased several applications of ship landmarks, including ship recognition, ship image generation, key area detection for ships, and ship detection. Project web page: https://vsislab.github.io/Ships_VSIS/.

I. Introduction

Ships play an irreplaceable role in transportation by carrying over 80% of the world’s trade [1]. It is thus important to monitor ship positions and navigation status for safety and economic reasons. For a considerable period of time in the past, ship monitoring was mainly done by full-time maritime staff, who may be fatigued after working for a long time, resulting in the inability to achieve sustainable monitoring. Over the past decade, the burst of artificial intelligence techniques has led to the rapid development of unmanned means of ship monitoring, where ship perception usually takes an important role [2], [3], [4], [5].