Fine-MVO: Toward Fine-Grained Feature Enhancement for Self-Supervised Monocular Visual Odometry in Dynamic Environments-Reference-Cited by-同舟云学术

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Fine-MVO: Toward Fine-Grained Feature Enhancement for Self-Supervised Monocular Visual Odometry in Dynamic Environments

Published:2024 Issue: Volume: Page:1-14
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Wei Wenhui¹^ORCID,Ping Yang²,Li Jiadong³^ORCID,Liu Xin³^ORCID,Zhou Yangfan³^ORCID

Affiliation:

1. School of Nano-Tech and Nano-Bionics, University of Science and Technology of China, Hefei, China

2. Academy of Military Sciences, Beijing, China

3. Suzhou Institute of Nano-Tech and Nano-Bionics (SINANO), Chinese Academy of Sciences, Suzhou, China

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Jiangsu Funding Program for Excellent Postdoctoral Talent

National Key Research and Development Program of China

Science and Technology Program of Suzhou

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6979/4358928/10549972.pdf?arnumber=10549972

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