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12 November 2024 Research on quality evaluation of 3D reconstruction model empowered by AI algorithm
Weihui Zhang, Rongyi Wang, Zhipeng Ren, Cheng Liao, Yanqi Huang, Shaobin Wang
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Proceedings Volume 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) ; 133952D (2024) https://doi.org/10.1117/12.3048372
Event: International Conference on Optics, Electronics, and Communication Engineering, 2024, Wuhan, China
Abstract
This paper evaluates four AI-based 3D reconstruction algorithms—TripoSR, Meshy, Instant, and One-2-34—alongside the traditional AR-Code method (which uses scanning for model point cloud reconstruction). By comparing the integrity ratio from point cloud data, depth information from depth maps, and perceived similarity from model dimensions, we identify the AI algorithm that best reconstructs 3D models. This research aligns with the “Opinions on Promoting the Implementation of the National Cultural Digitization Strategy” and provides actionable cases, methods, and strategies. It has practical applications in cultural heritage preservation, product design, and the digital transformation of smart cities, offering resource efficiency and enhanced user experiences in digital environments.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Weihui Zhang, Rongyi Wang, Zhipeng Ren, Cheng Liao, Yanqi Huang, and Shaobin Wang "Research on quality evaluation of 3D reconstruction model empowered by AI algorithm", Proc. SPIE 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) , 133952D (12 November 2024); https://doi.org/10.1117/12.3048372
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KEYWORDS
3D modeling
Reconstruction algorithms
Evolutionary algorithms
Artificial intelligence
Data modeling
Autoregressive models
Point clouds
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