@inproceedings{810aca4426d142e3b425cb65dc4ab3a3,
title = "Fusion network for face-based age estimation",
abstract = "Convolutional Neural Networks (CNN) have been applied to age-related research as the core framework. Although faces are composed of numerous facial attributes, most works with CNNs still consider a face as a typical object and do not pay enough attention to facial regions that carry age-specific feature for this particular task. In this paper, we propose a novel CNN architecture called Fusion Network (Fusion-Net) to tackle the age estimation problem. Apart from the whole face image, the FusionNet successively takes several age-specific facial patches as part of the input to emphasize the age-specific features. Through experiments, we show that the FusionNet significantly outperforms other state-of-the-art models on the MORPH II benchmark.",
keywords = "Age Estimation, Convolutional Neural Network, Feature Extraction, Soft Biometrics",
author = "Haoyi Wang and Xingjie Wei and Victor Sanchez and Li, {Chang Tsun}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 25th IEEE International Conference on Image Processing, ICIP 2018 ; Conference date: 07-10-2018 Through 10-10-2018",
year = "2018",
month = aug,
day = "29",
doi = "10.1109/ICIP.2018.8451606",
language = "English",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "2675--2679",
booktitle = "2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings",
address = "United States",
}