Age Synthesis and Estimation via Faces: A Survey

By Yun Fu, Guo-qing Guo, Thomas S. Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010

780 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/22f4b7fc6d89cfb3015c1d789047eb4007fca1ed

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In Computer Vision and Pattern Recognition

Citations in the corpus

A survey on face detection in the wild: Past, present and future (2015, background): “, gender/age recognition [5] and assessment of beauty [6]), face relighting and morphing [7], facial shape reconstruction [8], image and video retrieval, as well as organization and presentation of digital photo-albums [9].”
Learning ordinal discriminative features for age estimation (2012, background): “In recent years, human age estimation attracted much attention in the communities of computer vision and pattern recognition due to its potential applications in softbiometrics [8], human-computer interaction (HCI) [11], security control [8], surveillance monitoring [24], and electronic customer rel”
Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach (2017, background): “Due to limited space, we refer interested readers to reviews of the prior work on single facial attribute estimation in [10], [12], [14], [15], [39], [40], [41], [42].”
Age and gender classification using convolutional neural networks (2015, background): “A detailed survey of such methods can be found in [11] and, more recently, in [21].”
Face aging with conditional generative adversarial networks (2017, background): “Face aging, also known as age synthesis [1] and age progression [2], is defined as aesthetically rendering a face image with natural aging and rejuvenating effects on the individual face [1].”
What Else Does Your Biometric Data Reveal? A Survey on Soft Biometrics (2016, background): “[54] that focuses on automated analysis of age progression, discussing automated age synthesis and also age estimation techniques.”
Age , Gender and Race Estimation from Unconstrained Face Images (2014, methodology): “As a result, studies on the exploration of various attributes (other than the identity) embodied in a face image, such as age, gender, and race, have drawn increasing attention [2]–[5].”
Facial Age Estimation by Learning from Label Distributions (2010, background): “Hence developing automatic facial age estimation methods that are comparable or even superior to the human ability in age estimation has become an attractive yet challenging topic emerging in recent years [9].”
Deep Identity-aware Transfer of Facial Attributes (2016, methodology): “For age progression, explicit and implicit synthesis methods have been proposed for different image models [8, 19].”
ChaLearn Looking at People and Faces of the World: Face AnalysisWorkshop and Challenge 2016 (2016, background): “In the remainder of this paper, we describe in more detail the three face analysis challenges, their relevance in the context of the state of the art, and describe the results achieved by the winners of the challenges.”
50 years of biometric research: Accomplishments, challenges, and opportunities (2016, neutral): “In 1892,”
Age and Gender Estimation of Unfiltered Faces (2014, methodology): “cation domain, can be a regression problem or a multi-label classification task [9].”
A Comprehensive Survey to Face Hallucination (2013, background): “N. Wang · X. Gao · J. Li VIPS Lab, School of Electronic Engineering, Xidian University, Xi’an 710071, People’s Republic of China e-mail: nannanwang.xidian@gamil.com X. Gao e-mail: xbgao@mail.xidian.edu.cn J. Li e-mail: leejie@mail.xidian.edu.cn D. Tao Centre for Quantum Computation & Intelligent Sys”
Demographic Estimation from Face Images: Human vs. Machine Performance (2015, methodology): “Most of the age estimation methods published prior to 2011 are reviewed in [16].”
Cumulative Attribute Space for Age and Crowd Density Estimation (2013, methodology): “It is known [10] that at earlier ages, the human aging process is mainly reflected by the facial bone change (getting mature) resulting in shape changes.”