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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Manga face detection based on deep neural networks fusing global and local information
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Manga face detection based on deep neural networks fusing global and local information

机译:基于深神经网络融合全球和地方信息的漫画人体探测

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摘要

As more and more digitized manga (Japanese comics) books are available, efficient and effective access to manga is urgently needed. Among various elements of manga, character's face plays one of the most important roles in access and retrieval. We propose a deep neural network method to do manga face detection, which is a challenging but relatively unexplored topic. Given a manga page, we first find candidate regions based on the selective search scheme. Three convolutional neural networks are then proposed to detect manga faces of various appearance. We extract information from the entire object region and several local regions, and integrate multi-scale information in an early fusion manner or a late fusion manner. The proposed methods are evaluated based on a large-scale benchmark. Convincing performance compared to the state-of-the-art face detection modules designed for human faces is demonstrated. (C) 2018 Elsevier Ltd. All rights reserved.
机译:随着越来越多的数字化漫画(日本漫画)书籍,迫切需要高效,有效地访问漫画。 在漫画的各种元素中,角色的脸部扮演了访问和检索中最重要的角色之一。 我们提出了一种深入的神经网络方法来进行漫画人脸检测,这是一个具有挑战性但相对未开发的话题。 鉴于漫画页面,我们首先找到基于选择性搜索方案的候选地区。 然后提出了三个卷积神经网络以检测各种外观的漫步面。 我们从整个物体区域和几个本地区域提取信息,并以早期融合方式或晚期融合方式集成多尺度信息。 所提出的方法是基于大规模基准进行评估。 令人信服的性能与设计用于人面设计的最先进的面部检测模块相比。 (c)2018年elestvier有限公司保留所有权利。

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