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Adversarial UV-Transformation Texture Estimation for 3D Face Aging.
- Source :
-
IEEE Transactions on Circuits & Systems for Video Technology . Jul2022, Vol. 32 Issue 7, p4338-4350. 13p. - Publication Year :
- 2022
-
Abstract
- Face aging aims to estimate aged facial textures given a certain face image. A number of 2D face-aging methods have been developed, but there have been few studies on 3D face aging, which would be valuable in several real-world applications. The lack of 3D face-aging data has had a significant impact on the development of 3D face aging, but we hypothesized that the large amounts of 2D face-aging data on the internet could be leveraged for 3D aged facial textures. In this paper, we propose a novel 3D aging framework, which we call UV-transformation texture estimation based on generative adversarial networks (UVTE-GAN), to achieve 3D face aging. Specifically, the proposed framework has three parts: 1) a 3D vertex and texture estimator, which accurately estimates the face’s spatial vertices and textures; 2) a texture-aging GAN, which is responsible for aging the estimated texture map via adversarial learning; and 3) a 2D & 3D rendering rebuilder, which recovers 2D & 3D faces using the estimated facial vertex map and aged facial texture map. In addition, we also design a plugin layer that allows us to train the whole model in an end-to-end manner. Experimental results demonstrate the effectiveness of the proposed method in synthesizing visually pleasing 3D aged face pictures, and state-of-the-art performance is achieved on several public datasets. [ABSTRACT FROM AUTHOR]
- Subjects :
- *GENERATIVE adversarial networks
*FACE
*TEXTURE mapping
*AGING
*TEXTURES
Subjects
Details
- Language :
- English
- ISSN :
- 10518215
- Volume :
- 32
- Issue :
- 7
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Circuits & Systems for Video Technology
- Publication Type :
- Academic Journal
- Accession number :
- 157765777
- Full Text :
- https://doi.org/10.1109/TCSVT.2021.3133313