The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Personalized Age Progression with Bi-Level Aging Dictionary Learning
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“There are two main approaches to studying age progression: prototyping-based age progression and modelling-based age progression [14].”
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 [14]
In the citing paper
“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 [14]
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Cites
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Cited by
Sorted by citations
A Robust GAN-Generated Face Detection Method Based on Dual-Color Spaces and an Improved Xception
Chen, B., Liu, X., Zheng, Y., Zhao, G., & Shi, Y.-Q. (2022) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2021.3116679 · Cited by 125
Koudelová, J., Hoffmannová, E., Dupej, J., & Velemínská, J. (2019) · PLOS ONE · doi:10.1371/journal.pone.0212618 · Cited by 33
Metadata
- Authors
- Shu, X., Tang, J., Li, Z., Lai, H., Zhang, L., & Yan, S.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2018-04-01
- Volume
- 40
- Issue
- 4
- Pages
- 905-917
- ISSN
- 0162-8828
- 2160-9292
- Cited by
- 95
- References
- 1
- Funders
- 973 Program (2014CB347600))
- National Natural Science Foundation of China (61522203, 61572252, 61672285)
- Natural Science Foundation of Jiangsu Province (BK20140058, BK20150755)
- National Ten Thousand Talent Program of China
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