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Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation
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Most authors have used face ageing datasets consisting of photographs.
“Most authors have used face ageing datasets consisting of photographs, for example AGFW, CACD, FG-Net or MORPH [14–17].”
From Simulation of facial growth based on longitudinal data: Age progression and age regression between 7 and 17 years of age using 3D surface data (2019) · cites this paper as [17]
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Research works printed but not linked: 41
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Cited by
Sorted by citations
Attribute-Aware Face Aging With Wavelet-Based Generative Adversarial Networks
Liu, Y., Li, Q., & Sun, Z. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01215 · Cited by 156
“These four methods are (from left to right): CONGRE [18], HFA [26], GLCA-GAN [9], and PAG-GAN [25].”
MethodKoudelová, J., Hoffmannová, E., Dupej, J., & Velemínská, J. (2019) · PLOS ONE · doi:10.1371/journal.pone.0212618 · Cited by 33
Metadata
- Authors
- Yang, H., Huang, D., Wang, Y., Wang, H., & Tang, Y.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2016-06
- Volume
- 25
- Issue
- 6
- Pages
- 2493-2507
- ISSN
- 1057-7149
- 1941-0042
- Cited by
- 58
- References
- 0
- Funders
- Hong Kong, Macao, and Taiwan Science and Technology Cooperation Program of China (L2015TGA9004)
- Specialized Research Fund for the Doctoral Program of Higher Education (20121102120016)
- Fundamental Research Funds for the Central Universities
- National Natural Science Foundation of China (61273263, 61540048, 61421003)
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