@inproceedings{54bc14b044d94c99b658f52a33ade397,
title = "Facial landmark detection via cascade multi-channel convolutional neural network",
abstract = "This paper presents a novel cascade multi-channel convolutional neural networks(CMC-CNN) approach for face alignment. Several CNN are jointly used for the finally output. In our method, each stage CNN takes the local region around the landmarks as input, and each local patches does convolution separately, which can lead network to learn local high-level features. Then a fully connected layer is put to learn global information from these local features. Our methods has achieves the state-of-the-art results when tested on the 300 Face in-the-Wild(300-W) dataset.",
keywords = "CMC-CNN, Face Alignment, Global Feature, Local Feature",
author = "Qiqi Hou and Jinjun Wang and Lele Cheng and Yihong Gong",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Image Processing, ICIP 2015 ; Conference date: 27-09-2015 Through 30-09-2015",
year = "2015",
month = dec,
day = "9",
doi = "10.1109/ICIP.2015.7351111",
language = "英语",
series = "Proceedings - International Conference on Image Processing, ICIP",
publisher = "IEEE Computer Society",
pages = "1800--1804",
booktitle = "2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings",
}