CASIA OpenIR  > 模式识别国家重点实验室  > 图像与视频分析
Adaptive Variance Based Label Distribution Learning For Facial Age Estimation
Wen Xin1,2; Li Biying1,2; Guo Haiyun1; Liu Zhiwei1; Hu Guosheng3; Tang Ming1; Wang Jinqiao1
Conference NameEuropean Conference on Computer Vision
Conference Date2020-08
Conference Placeonline
Publication PlaceSwitzerland
Estimating age from a single facial image is a classic and
challenging topic in computer vision. One of its most intractable issues
is label ambiguity, i.e., face images from adjacent age of the same person
are often indistinguishable. Some existing methods adopt distribution
learning to tackle this issue by exploiting the semantic correlation be
tween age labels. Actually, most of them set a fifixed value to the variance
of Gaussian label distribution for all the images. However, the variance is
closely related to the correlation between adjacent ages and should vary
across ages and identities. To model a sample-specifific variance, in this pa
per, we propose an adaptive variance based distribution learning (AVDL)
method for facial age estimation. AVDL introduces the data-driven op
timization framework, meta-learning, to achieve this. Specififically, AVDL
performs a meta gradient descent step on the variable (i.e. variance)
to minimize the loss on a clean unbiased validation set. By adaptively
learning proper variance for each sample, our method can approximate
the true age probability distribution more effffectively. Extensive experi
ments on FG-NET and MORPH II datasets show the superiority of our
proposed approach to the existing state-of-the-art methods.
Keywordage estimation distribution learning meta-learning
Indexed ByEI
Document Type会议论文
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
2.School of Artificial Intelligence, University of Chinese Academy of Sciences
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wen Xin,Li Biying,Guo Haiyun,et al. Adaptive Variance Based Label Distribution Learning For Facial Age Estimation[C]. Switzerland:Springer,2020.
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