Trash-ICRA19 Dataset

The authors create a large and publicly-available Trash-ICRA19: A Bounding Box Labeled Dataset of Underwater Trash of actual debris in open-water locations is annotated for training a number of convolutional neural network architectures for object detection. This data was sourced from the J-EDI dataset of marine debris. The videos that comprise that dataset vary greatly in quality, depth, objects in scenes, and the cameras used. They contain images of many different types of marine debris, captured from real-world environments, providing a variety of objects in different states of decay, occlusion, and overgrowth. Additionally, the clarity of the water and quality of the light vary significantly from video to video. These videos were processed to extract 5,700 images, which comprise this dataset, all labeled with bounding boxes on instances of _plastic_ trash, biological objects such as plants and animals (_bio_), and _rov_.

作者构建了一个大型且可供公众访问的 Trash-ICRA19 数据集：一个标注了真实海洋漂浮垃圾边界框的水下垃圾数据集。该数据集旨在为训练多种卷积神经网络架构进行目标检测提供训练材料。数据源自海洋垃圾的 J-EDI 数据集。构成该数据集的视频在画质、水深、场景中的物体以及所使用的摄像机方面存在显著差异。这些视频包含了多种类型的海洋垃圾图像，这些图像是从现实世界环境中捕获的，提供了处于不同分解、遮挡和过度生长状态的物体多样性。此外，视频中的水质清晰度和光线质量也存在着显著的差异。通过对这些视频进行处理，共提取了 5,700 张图像，构成了本数据集，所有图像均标注了塑料垃圾（_plastic_）、生物物体（如植物和动物，_bio_）以及水下遥控航行器（_rov_）的边界框。

搜集汇总

背景与挑战

背景概述

Trash-ICRA19数据集是一个专注于水下垃圾检测的目标检测数据集，发布于2018年，包含7,684张图像和11,061个标注对象，分为塑料、生物和ROV三个类别。该数据集源自真实海洋环境的视频，图像尺寸为480x320像素，具有水质、光照和物体状态多样性，旨在支持自主水下航行器进行垃圾识别和清理，应用于环保和机器人领域。