Related papers: A Survey on RGB-D Datasets

A Survey on RGB-D Datasets

URL: http://arxiv.org/abs/2201.05761v1
Date: Sat, 15 Jan 2022 05:35:19 GMT
Title: A Survey on RGB-D Datasets
Authors: Alexandre Lopes, Roberto Souza, Helio Pedrini
Abstract summary: 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.
Score: 69.73803123972297
License: http://creativecommons.org/licenses/by/4.0/
Abstract: 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.

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