TrashCan 1.0 An Instance-Segmentation Labeled Dataset of Trash Observations

The TrashCan dataset is comprised of annotated images (7,212 images currently) which contain observations of trash, ROVs, and a wide variety of undersea flora and fauna. The annotations in this dataset take the format of instance segmentation annotations: bitmaps containing a mask marking which pixels in the image contain each object. The imagery in TrashCan is sourced from the J-EDI (JAMSTEC E-Library of Deep-sea Images) dataset, curated by the Japan Agency of Marine Earth Science and Technology (JAMSTEC). This dataset contains videos from ROVs operated by JAMSTEC since 1982, largely in the sea of Japan. The dataset has two versions, TrashCan-Material and TrashCan-Instance, corresponding to different object class configurations. The eventual goal is to develop efficient and accurate trash detection methods suitable for onboard robot deployment. While datasets have previously been created containing bounding box level annotations of trash in marine environments, TrashCan is, to the best of our knowledge, the first instance-segmentation annotated dataset of underwater trash. It is our hope that the release of this dataset will facilitate further research on this challenging problem, bringing the marine robotics community closer to a solution for the urgent problem of autonomous trash detection and removal.

TrashCan数据集由带标注的图像构成（当前共7212张），图像涵盖海洋垃圾、遥控无人潜水器（Remotely Operated Vehicle，简称ROV）及各类海底动植物。该数据集的标注采用实例分割标注格式：通过位图掩码标记图像中对应各目标的像素区域。TrashCan数据集的图像源自J-EDI（日本海洋科技中心深海图像电子图书馆，JAMSTEC E-Library of Deep-sea Images）数据集，该数据集由日本海洋地球科学技术厅（Japan Agency of Marine Earth Science and Technology，简称JAMSTEC）整理编制。该数据集收录了JAMSTEC自1982年起使用ROV采集的视频数据，采集区域主要集中于日本海。本数据集包含两个版本：TrashCan-Material与TrashCan-Instance，二者对应不同的目标类别配置方案。本数据集的最终研发目标是开发适用于机器人机载部署的高效精准海洋垃圾检测方法。尽管此前已有研究构建了包含海洋垃圾边界框级标注的数据集，但据我们所知，TrashCan是首个面向水下垃圾的实例分割标注数据集。我们期望本数据集的发布能够推动该挑战性课题的后续研究，助力海洋机器人领域早日攻克自主海洋垃圾检测与清除这一紧迫难题。