期刊
SIGNAL IMAGE AND VIDEO PROCESSING
卷 14, 期 7, 页码 1345-1353出版社
SPRINGER LONDON LTD
DOI: 10.1007/s11760-020-01680-w
关键词
Face detection; CNN; Transfer learning; NMS
In this paper, we introduce a deep learning (CNN) based method for face detection in an uncontrolled environment. The proposed method consists in developing a CNN architecture dedicated to the face detection tasks by combining both of global and local features at multiple scales. Our architecture is composed of two main networks: A region proposal network that generates a list of regions of interest (ROIs) and a second corresponds to a network that use these ROIs for classification into face/non-face. Both of them share the full-image convolution features of a pre-trained ResNet-50 model. Experimental study was conducted on the famous WIDER Face and FDDB databases. The obtained results proved the efficiency as well as the feasibility of the proposed method to deal with multi-scale face detection problems.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据