3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose From Monocular Video-Reference-Cited by-同舟云学术

3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose From Monocular Video

Published:2023-04 Issue:4 Volume:33 Page:1776-1786
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Wang Guangming¹^ORCID,Zhong Jiquan¹^ORCID,Zhao Shijie²,Wu Wenhua¹,Liu Zhe³^ORCID,Wang Hesheng¹^ORCID

Affiliation:

1. Department of Automation, Key Laboratory of System Control and Information Processing of Ministry of Education, Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education, Shanghai Engineering Research Center of Intelligent Control and Management, Shanghai Jiao Tong University, Shanghai, China

2. Department of Engineering Mechanics, Shanghai Jiao Tong University, Shanghai, China

3. MOE Key Laboratory of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China

Funder

Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Open Research Projects of Zhejiang Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10091959/09924173.pdf?arnumber=9924173

Reference64 articles.

1. Unsupervised scale-consistent depth and ego-motion learning from monocular video;bian;Proc NIPS,2019

2. Learning Stereo from Single Images

3. Unsupervised Learning of Monocular Depth and Ego-Motion Using Multiple Masks

4. Image Quality Assessment: From Error Visibility to Structural Similarity

5. Depth From Videos in the Wild: Unsupervised Monocular Depth Learning From Unknown Cameras

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