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.
翻译:RGB-D数据对于解决计算机视野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开 RGB-D数据集,如室内、室外、空中、驾驶和医疗等。这些数据集对不同应用有用,对于处理典型的计算机视野任务(如单眼深度估计)至关重要。本文审查和分类了图像数据集,其中包括深度信息。我们收集了203个数据集,其中载有可获取的数据,并将其分为三类:场景/对象、身体和医学。我们还概述了不同类型的传感器、深度应用,我们研究了使用和创建包含深度数据的数据集的趋势和未来方向,以及如何应用这些数据集来调查单眼深度估计领域的通用机器学习模型的开发情况。