Generating High Resolution Depth Image from Low Resolution LiDAR Data using RGB Image

Kento Yamakawa; Fumihiko Sakaue; Jun Sato

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Paper

Generating High Resolution Depth Image from Low Resolution LiDAR Data using RGB Image

Topics: Image Enhancement and Restoration; Multimodal and Multi-Sensor Models of Image Formation

In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, 659-665, 2022

Authors: Kento Yamakawa ; Fumihiko Sakaue and Jun Sato

Affiliation: Nagoya Institute of Technology, Japan

Keyword(s): Depth Image, RGB Image, High Resolution, GAN.

Abstract: In this paper, we propose a GAN that generates a high-resolution depth image from a low-resolution depth image obtained from low-resolution LiDAR. Our method uses a high-resolution RGB image as a guide image, and generate high-resolution depth image from low-resolution depth image efficiently by using GAN. The results of the qualitative and quantitative evaluation show the effectiveness of the proposed method.

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Paper citation in several formats:

Yamakawa, K.; Sakaue, F. and Sato, J. (2022). Generating High Resolution Depth Image from Low Resolution LiDAR Data using RGB Image. 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 659-665. DOI: 10.5220/0010903900003124

@conference{visapp22,
author={Kento Yamakawa. and Fumihiko Sakaue. and Jun Sato.},
title={Generating High Resolution Depth Image from Low Resolution LiDAR Data using RGB Image},
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={659-665},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010903900003124},
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 - Generating High Resolution Depth Image from Low Resolution LiDAR Data using RGB Image
SN - 978-989-758-555-5
IS - 2184-4321
AU - Yamakawa, K.
AU - Sakaue, F.
AU - Sato, J.
PY - 2022
SP - 659
EP - 665
DO - 10.5220/0010903900003124
PB - SciTePress