Monocular Depth Estimation Based on Deep Learning:A Survey
Ruan Xiaogang, Yan Wenjing, Jing Huang, Peiyuan Guo, Wei Guo
Abstract
Monocular depth estimation relied on RGB images is an important ill posed problem in ithe 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.
Topics & Concepts
Artificial intelligenceMonocularComputer scienceComputer visionDeep learningConvolutional neural networkConvolution (computer science)SegmentationMonocular visionObject (grammar)EstimationObject detectionFace (sociological concept)PoseImage segmentationArtificial neural networkEngineeringSociologySocial scienceSystems engineeringAdvanced Vision and ImagingImage Processing Techniques and ApplicationsImage and Object Detection Techniques