VTAE: Variational Transformer Autoencoder With Manifolds Learning-Reference-Cited by-同舟云学术

VTAE: Variational Transformer Autoencoder With Manifolds Learning

Published:2023 Issue: Volume:32 Page:4486-4500
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Shamsolmoali Pourya¹^ORCID,Zareapoor Masoumeh²^ORCID,Zhou Huiyu³^ORCID,Tao Dacheng⁴,Li Xuelong⁵^ORCID

Affiliation:

1. School of Communication and Electronic Engineering, East China Normal University, Shanghai, China

2. School of Automation, Xi’an Jiao Tong University, Xi’an, China

3. School of Computing and Mathematical Sciences, University of Leicester, Leicester, U.K

4. Faculty of Engineering, School of Computer Science, The University of Sydney, Darlington, NSW, Australia

5. Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, and the School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi’an, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10201469.pdf?arnumber=10201469

Reference74 articles.

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4. High-Fidelity Pluralistic Image Completion with Transformers

5. Unsupervised learning of group invariant and equivariant representations;winter;Proc Adv Neural Inf Process Syst,2022

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