A Survey on RGB-D Datasets
원문 초록
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.
함께 살펴볼 논문
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MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised Training
TR2M: Transferring Monocular Relative Depth to Metric Depth with Language Descriptions and Scale-Oriented Contrast
Always Clear Depth: Robust Monocular Depth Estimation under Adverse Weather
Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis
LiftFeat: 3D Geometry-Aware Local Feature Matching
토론
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