Age Estimation is the task of estimating the age of a person from an image.
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Extraordinary progress has been made towards developing neural network architectures for classification tasks.
SOTA for Age Estimation on UTKFace
However, it is difficult to collect sufficient training images with precise labels in some domains such as apparent age estimation, head pose estimation, multi-label classification and semantic segmentation.
SOTA for Age Estimation on ChaLearn 2015
Residual representation learning simplifies the optimization problem of learning complex functions and has been widely used by traditional convolutional neural networks.
Our model outperformed a state-of-the-art architecture proposed to separately address apparent and real age regression.
Recently, MobileNets and ShuffleNets have been proposed to reduce the number of parameters, yielding lightweight models.