论文标题
RGB-D数据集的调查
A Survey on RGB-D Datasets
论文作者
论文摘要
RGB-D数据对于解决计算机视觉中的许多问题至关重要。已经提出了数百个包含各种场景的公共RGB-D数据集，例如室内，室外，空中，驾驶和医疗。这些数据集对不同的应用程序很有用，并且对于解决经典的计算机视觉任务（例如单眼深度估计）至关重要。本文审查并分类了包括深度信息的图像数据集。我们收集了203个数据集，其中包含可访问的数据，并将它们分为三类：场景/对象，身体和医疗。我们还概述了不同类型的传感器，深度应用程序，并研究了包含深度数据的数据集的使用和创建的趋势和未来方向，以及如何应用它们来研究单程深度估计领域中可概括的机器学习模型的开发。
RGB-D data is essential for solving many problems in computer vision. Hundreds of public RGB-D datasets containing various scenes, such as indoor, outdoor, aerial, driving, and medical, have been proposed. These datasets are useful for different applications and are fundamental for addressing classic computer vision tasks, such as monocular depth estimation. This paper reviewed and categorized image datasets that include depth information. We gathered 203 datasets that contain accessible data and grouped them into three categories: scene/objects, body, and medical. We also provided an overview of the different types of sensors, depth applications, and we examined trends and future directions of the usage and creation of datasets containing depth data, and how they can be applied to investigate the development of generalizable machine learning models in the monocular depth estimation field.
