论文标题
Kolomverse：韩国开放大型图像数据集，用于海上宇宙中的对象检测
KOLOMVERSE: Korea open large-scale image dataset for object detection in the maritime universe
论文作者
论文摘要
多年来，为各种对象检测任务开发了数据集。海事域中的对象检测对于船舶的安全和导航至关重要。但是，在海事域中仍然缺乏公开可用的大规模数据集。为了克服这一挑战，我们提出了Kolomverse，这是一个开放的大型图像数据集，可在Kriso（韩国研究所和海洋工程研究所）的海事域中进行对象检测。我们收集了从韩国21个领土水域捕获的5,845小时的视频数据。通过精心设计的数据质量评估过程，我们从视频数据中收集了大约2,151,470个4K分辨率图像。该数据集考虑了各种环境：天气，时间，照明，遮挡，观点，背景，风速和可见性。 Kolomverse由五个类（船，浮标，渔网浮标，灯塔和风电场）组成，用于海上对象检测。该数据集的图像为3840 $ \ times $ 2160像素，据我们所知，它是迄今为止最大的公开数据集，可在海上域中检测到对象检测。我们进行了对象检测实验，并在几个预训练的最先进的架构上评估了我们的数据集，以显示我们数据集的有效性和实用性。该数据集可在：\ url {https://github.com/maritimedataset/kolomverse}中获得。
Over the years, datasets have been developed for various object detection tasks. Object detection in the maritime domain is essential for the safety and navigation of ships. However, there is still a lack of publicly available large-scale datasets in the maritime domain. To overcome this challenge, we present KOLOMVERSE, an open large-scale image dataset for object detection in the maritime domain by KRISO (Korea Research Institute of Ships and Ocean Engineering). We collected 5,845 hours of video data captured from 21 territorial waters of South Korea. Through an elaborate data quality assessment process, we gathered around 2,151,470 4K resolution images from the video data. This dataset considers various environments: weather, time, illumination, occlusion, viewpoint, background, wind speed, and visibility. The KOLOMVERSE consists of five classes (ship, buoy, fishnet buoy, lighthouse and wind farm) for maritime object detection. The dataset has images of 3840$\times$2160 pixels and to our knowledge, it is by far the largest publicly available dataset for object detection in the maritime domain. We performed object detection experiments and evaluated our dataset on several pre-trained state-of-the-art architectures to show the effectiveness and usefulness of our dataset. The dataset is available at: \url{https://github.com/MaritimeDataset/KOLOMVERSE}.
