ImgAdaPoinTr: Improving Point Cloud Completion via Images and Segmentation

Vaagn Chopuryan; Mikhail Kuznetsov; Mikhail Kuznetsov; Vasilii Latonov; Natalia Semenova; Natalia Semenova

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

ImgAdaPoinTr: Improving Point Cloud Completion via Images and Segmentation

Topics: 3D Deep Learning; Image-Based Modeling and 3D Reconstruction; Segmentation and Grouping

In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, 47-58, 2024 , Rome, Italy

Authors: Vaagn Chopuryan ¹ ; Mikhail Kuznetsov ^{1

;

2} ; Vasilii Latonov ¹ and Natalia Semenova ^{1

;

3}

Affiliations: ¹ Sberbank PJSC, 19 Vavilova St., Moscow 117312, Russia ; ² National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), 31 Kashirskoe shosse, 31, Moscow 115409, Russia ; ³ AIRI, Nizhniy Susalnyy Lane 5, Moscow 105064, Russia

Keyword(s): Point Cloud Completion, Transformers, View-Guided, Segmentation.

Abstract: Point cloud completion is an essential task consisting of inferring and filling in missing parts of a 3D point cloud representation. In this paper, we present an ImgAdaPoinTr model, which extends the original Transformer encoder-decoder architecture by accurately incorporating visual information. Besides, we assumed using segmentation of 3D objects as a part of the pipeline due to acquiring an additional increase in performance. We also introduce the novel ImgPCN dataset generated by our rendering tool. The results show that our approach outperforms AdaPoinTr by average 2.9% and 10.3% in terms of Chamfer-Distance L1 and L2 metrics, respectively. The code and dataset are available via the link https://github.com/ImgAdaPoinTr.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 18.221.85.100

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Chopuryan, V.; Kuznetsov, M.; Latonov, V. and Semenova, N. (2024). ImgAdaPoinTr: Improving Point Cloud Completion via Images and Segmentation. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 47-58. DOI: 10.5220/0012398100003660

@conference{visapp24,
author={Vaagn Chopuryan. and Mikhail Kuznetsov. and Vasilii Latonov. and Natalia Semenova.},
title={ImgAdaPoinTr: Improving Point Cloud Completion via Images and Segmentation},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={47-58},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012398100003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - ImgAdaPoinTr: Improving Point Cloud Completion via Images and Segmentation
SN - 978-989-758-679-8
IS - 2184-4321
AU - Chopuryan, V.
AU - Kuznetsov, M.
AU - Latonov, V.
AU - Semenova, N.
PY - 2024
SP - 47
EP - 58
DO - 10.5220/0012398100003660
PB - SciTePress