Object Specific Deep Feature for Face Detection

Xianxu HOU  Jiasong ZHU  Ke SUN  Linlin SHEN  Guoping QIU  

IEICE TRANSACTIONS on Information and Systems   Vol.E101-D   No.5   pp.1270-1277
Publication Date: 2018/05/01
Publicized: 2018/02/16
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2017MVP0014
Type of Manuscript: Special Section PAPER (Special Section on Machine Vision and its Applications)
Category: Machine Vision and its Applications
deep feature,  convolutional neural network,  object specific channel,  face detection,  

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Motivated by the observation that certain convolutional channels of a Convolutional Neural Network (CNN) exhibit object specific responses, we seek to discover and exploit the convolutional channels of a CNN in which neurons are activated by the presence of specific objects in the input image. A method for explicitly fine-tuning a pre-trained CNN to induce object specific channel (OSC) and systematically identifying it for the human faces has been developed. In this paper, we introduce a multi-scale approach to constructing robust face heatmaps based on OSC features for rapidly filtering out non-face regions thus significantly improving search efficiency for face detection. We show that multi-scale OSC can be used to develop simple and compact face detectors in unconstrained settings with state of the art performance.