Multi-Scale Spatio-Temporal Feature Extraction and Depth Estimation from Sequences by Ordinal Classification

Multi-Scale Spatio-Temporal Feature Extraction and Depth Estimation from Sequences by Ordinal Classification

Depth estimation is a key problem in 3D computer vision and has a wide variety of applications. In this paper we explore whether deep learning network can predict depth map accurately by learning multi-scale spatio-temporal features from sequences and recasting the depth estimation from a regression...

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Bibliographic Details
Main Author: Yang Liu
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Sensors
Subjects:
depth prediction
deep learning
spatio-temporal feature extraction
ConvLSTM
ordinal classification
Online Access:https://www.mdpi.com/1424-8220/20/7/1979

Internet

https://www.mdpi.com/1424-8220/20/7/1979

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