Heterogeneous Feature Fusion Module Based on CNN and Transformer for Multiview Stereo Reconstruction

Rui Gao, Jiajia Xu, Yipeng Chen and Kyungeun Cho ()
Additional contact information
Rui Gao: Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Republic of Korea
Jiajia Xu: Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Republic of Korea
Yipeng Chen: Department of Autonomous Things Intelligence, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Republic of Korea
Kyungeun Cho: Department of Multimedia Engineering, Dongguk University-Seoul, 30, Pildongro-1-gil, Jung-gu, Seoul 04620, Republic of Korea

Mathematics, 2022, vol. 11, issue 1, 1-14

Abstract: For decades, a vital area of computer vision research has been multiview stereo (MVS), which creates 3D models of a scene using photographs. This study presents an effective MVS network for 3D reconstruction utilizing multiview pictures. Alternative learning-based reconstruction techniques work well, because CNNs (convolutional neural network) can extract only the image’s local features; however, they contain many artifacts. Herein, a transformer and CNN are used to extract the global and local features of the image, respectively. Additionally, hierarchical aggregation and heterogeneous interaction modules were used to improve these features. They are based on the transformer and can extract dense features with 3D consistency and global context that are necessary to provide accurate matching for MVS.

Keywords: multi-view stereo; 3D reconstruction; deep learning; transformer (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/1/112/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/1/112/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2022:i:1:p:112-:d:1015877

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().