发明名称 |
LEARNING DEEP FACE REPRESENTATION |
摘要 |
Face representation is a crucial step of face recognition systems. An optimal face representation should be discriminative, robust, compact, and very easy to implement. While numerous hand-crafted and learning-based representations have been proposed, considerable room for improvement is still present. A very easy-to-implement deep learning framework for face representation is presented. The framework bases on pyramid convolutional neural network (CNN). The pyramid CNN adopts a greedy-filter-and-down-sample operation, which enables the training procedure to be very fast and computation efficient. In addition, the structure of Pyramid CNN can naturally incorporate feature sharing across multi-scale face representations, increasing the discriminative ability of resulting representation. |
申请公布号 |
WO2015180042(A1) |
申请公布日期 |
2015.12.03 |
申请号 |
WO2014CN78553 |
申请日期 |
2014.05.27 |
申请人 |
BEIJING KUANGSHI TECHNOLOGY CO., LTD. |
发明人 |
YIN, QI;CAO, ZHIMIN;JIANG, YUNING;FAN, HAOQIANG |
分类号 |
G06F17/30;G06K9/00 |
主分类号 |
G06F17/30 |
代理机构 |
|
代理人 |
|
主权项 |
|
地址 |
|