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From Imperfection to Perfection: Advanced 3D Facial Reconstruction Using MICA Models and Self-Supervision Learning

by Thinh D. Le, Duong Q. Nguyen, Phuong D. Nguyen, H. Nguyen-Xuan*

CIRTECH Institute, HUTECH University, Ho Chi Minh City, 72308, Viet Nam

* Corresponding Author: H. Nguyen-Xuan. Email: email

(This article belongs to the Special Issue: Data-driven Additive Manufacturing: Methodology, Fabrication, and Applications )

Computer Modeling in Engineering & Sciences 2025, 142(2), 1459-1479. https://doi.org/10.32604/cmes.2024.056753

Abstract

Research on reconstructing imperfect faces is a challenging task. In this study, we explore a data-driven approach using a pre-trained MICA (MetrIC fAce) model combined with 3D printing to address this challenge. We propose a training strategy that utilizes the pre-trained MICA model and self-supervised learning techniques to improve accuracy and reduce the time needed for 3D facial structure reconstruction. Our results demonstrate high accuracy, evaluated by the geometric loss function and various statistical measures. To showcase the effectiveness of the approach, we used 3D printing to create a model that covers facial wounds. The findings indicate that our method produces a model that fits well and achieves comprehensive 3D facial reconstruction. This technique has the potential to aid doctors in treating patients with facial injuries.

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APA Style
Le, T.D., Nguyen, D.Q., Nguyen, P.D., Nguyen-Xuan, H. (2025). From imperfection to perfection: advanced 3D facial reconstruction using MICA models and self-supervision learning. Computer Modeling in Engineering & Sciences, 142(2), 1459–1479. https://doi.org/10.32604/cmes.2024.056753
Vancouver Style
Le TD, Nguyen DQ, Nguyen PD, Nguyen-Xuan H. From imperfection to perfection: advanced 3D facial reconstruction using MICA models and self-supervision learning. Comput Model Eng Sci. 2025;142(2):1459–1479. https://doi.org/10.32604/cmes.2024.056753
IEEE Style
T. D. Le, D. Q. Nguyen, P. D. Nguyen, and H. Nguyen-Xuan, “From Imperfection to Perfection: Advanced 3D Facial Reconstruction Using MICA Models and Self-Supervision Learning,” Comput. Model. Eng. Sci., vol. 142, no. 2, pp. 1459–1479, 2025. https://doi.org/10.32604/cmes.2024.056753



cc Copyright © 2025 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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