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Authors: Milena Gazdieva 1 ; Oleg Voynov 1 ; Alexey Artemov 1 ; Youyi Zheng 2 ; Luiz Velho 3 and Evgeny Burnaev 1

Affiliations: 1 Skolkovo Institute of Science and Technology, Moscow, Russia ; 2 State Key Lab, Zhejiang University, Hangzhou, China ; 3 Instituto Nacional de Matemática Pura e Aplicada, Rio de Janeiro, Brazil

Keyword(s): Depth Super-Resolution, Neural Regularization, 3D Deep Learning.

Abstract: Depth maps captured with commodity sensors often require super-resolution to be used in applications. In this work we study a super-resolution approach based on a variational problem statement with Tikhonov regularization where the regularizer is parametrized with a deep neural network. This approach was previously applied successfully in photoacoustic tomography. We experimentally show that its application to depth map super-resolution is difficult, and provide suggestions about the reasons for that.

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Paper citation in several formats:
Gazdieva, M.; Voynov, O.; Artemov, A.; Zheng, Y.; Velho, L. and Burnaev, E. (2022). Can We Use Neural Regularization to Solve Depth Super-resolution?. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5; ISSN 2184-4321, SciTePress, pages 582-590. DOI: 10.5220/0010883500003124

@conference{visapp22,
author={Milena Gazdieva. and Oleg Voynov. and Alexey Artemov. and Youyi Zheng. and Luiz Velho. and Evgeny Burnaev.},
title={Can We Use Neural Regularization to Solve Depth Super-resolution?},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={582-590},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010883500003124},
isbn={978-989-758-555-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Can We Use Neural Regularization to Solve Depth Super-resolution?
SN - 978-989-758-555-5
IS - 2184-4321
AU - Gazdieva, M.
AU - Voynov, O.
AU - Artemov, A.
AU - Zheng, Y.
AU - Velho, L.
AU - Burnaev, E.
PY - 2022
SP - 582
EP - 590
DO - 10.5220/0010883500003124
PB - SciTePress

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