Monocular Depth Estimation Based on Deep Learning:A Survey

被引：18
作者：
Ruan Xiaogang [1 ,2 ]
Yan Wenjing [1 ,2 ]
Huang Jing [1 ,2 ]
Guo Peiyuan [1 ,2 ]
Guo Wei [1 ,2 ]
机构：
[1] BJUT, Inst Artificial Intelligence & Robot, Beijing, Peoples R China
[2] BJUT, Fac Informat Technol, Beijing, Peoples R China
来源：
2020 CHINESE AUTOMATION CONGRESS (CAC 2020) | 2020年
关键词：
monocular depth estimation; convolutional neural networks; deep learning; RGB images;
D O I：
10.1109/CAC51589.2020.9327548
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Monocular depth estimation relied on RGB images is an important ill posed problem in the system of computer vision. Recently, people use the method of deep learning to discuss this problem. Most of the existing monocular depth estimation algorithms relied on convolution neural network. Depth estimation based on 2D images has important applications in image segmentation, 3D object detection, robot navigation, object tracking and autonomous driving. This paper gives a brief overview of this problem, reviews, evaluates and discusses the monocular depth estimation algorithms relied on deep learning, and looks forward to the direction of further research in the face of some challenges.
引用
收藏
页码：2436 / 2440
页数：5
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