All systems operational
Q1 2026

HyVDAR: A semi-supervised framework for high-fidelity 3D object reconstruction from sparse multi-view point clouds in virtual reality applications

Shanglin Li · Juan Xiao
10.1016/j.eij.2026.100906 404 Views 0 Citations
0
Citations
404
Views
Abstract not available for this publication.
Cite this Article (APA)
Shanglin, L., Juan, X. (2026). HyVDAR: A semi-supervised framework for high-fidelity 3D object reconstruction from sparse multi-view point clouds in virtual reality applications. Egyptian Informatics Journal. https://doi.org/10.1016/j.eij.2026.100906
Related Papers
91
cites
1,955
45
cites
2,441
29
cites
948
18
cites
428
Enhancing personalization in IoT-based health monitoring via generative AI and transfer learning
Rupali Atul Mahajan; Rajesh Dey; Mudassir Khan; Mazliham Mohd Su’ud; Muhammad Ma · 2025
15
cites
423
Access
View Full Text via DOI
Published in
ISSN 1110-8665
Quartile Q1
AMS Score 100
Field Computer Science & AI
Publisher Cairo University / Elsevier
Country 🇪🇬 Egypt
View Journal Profile →
Authors
Publication Details
Year 2026
Language English
Added 24 Jul 2026