Face Modeling Based on Deep Learning and Traditional Methods: A Survey

Abstract. 3D face modeling, as an important research field in computer graphics and vision, has undergone remarkable development in recent years. The technology is widely used in various scenarios, like film and television production, virtual reality, augmented reality, facial recognition, security monitoring, and medical diagnosis. This paper aims to systematically explore the main technologies of 3D face modeling, especially the application and development of deep learning methods in it, review traditional face modeling methods, introduce in detail the latest technical advances based on deep learning, and analyze the advantages and disadvantages of these methods in practical applications.

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Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-08
DOI
https://doi.org/10.54254/2755-2721/81/20241149
Citations
5
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
1.25
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article

Face Modeling Based on Deep Learning and Traditional Methods: A Survey

Yuqian Zhang
5 citations
Applied and Computational Engineering
Face recognition and analysis
1.25
article

Face Modeling Based on Deep Learning and Traditional Methods: A Survey

Yuqian Zhang
article en
5 citations

Abstract

Abstract. 3D face modeling, as an important research field in computer graphics and vision, has undergone remarkable development in recent years. The technology is widely used in various scenarios, like film and television production, virtual reality, augmented reality, facial recognition, security monitoring, and medical diagnosis. This paper aims to systematically explore the main technologies of 3D face modeling, especially the application and development of deep learning methods in it, review traditional face modeling methods, introduce in detail the latest technical advances based on deep learning, and analyze the advantages and disadvantages of these methods in practical applications.

Applied and Computational EngineeringVol. 81(1)
Shijiazhuang Tiedao University (CN)
Openalex Percentile: Top 18%
Face recognition and analysis
1.25
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