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Picture News Collection: A Dataset for Automatic Picture News Thumbnail Selection

机译:图片新闻集合:自动图片新闻缩略图选择的数据集

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Picture news has become more and more popular among online news in recent years. As the first impression to viewers, thumbnail plays a very important role in picture news. However, it is time consuming to manually select thumbnails for a huge amount of picture news. In this paper, we introduce a new task of automatic picture news thumbnail selection. Given a piece of picture news containing a set of images, this task is to select several appropriate images from the picture news as candidate thumbnails. To this end, we present a large publicly available image dataset for this task, called Picture News Collection (The Picture News Collection 0.1 version can be publicly available online at https://github.com/anonymity01/Picture-News-Collection.). The Picture News Collection contains more than 4 million images of 347,731 picture news from two famous news websites, Sina News and NetEase News. Selecting good enough thumbnails is complicated and needs to consider many aspects, such as attraction, hot topics, content integrity, etc. In order to select appropriate candidate thumbnails, we propose an attention-based thumbnail selection model, and the experimental results comparing with three image classification based baselines show that our proposed methods outperform the baselines. We introduce the automatic picture news thumbnail selection task and the dataset to encourage further studies of this challenge.
机译:图片新闻近年来在线新闻中变得越来越受欢迎。作为观众的第一印象,缩略图在图片新闻中起着非常重要的作用。但是,为了手动选择缩略图以获得大量图片新闻是耗时的。在本文中,我们介绍了自动图片新闻缩略图选择的新任务。鉴于包含一组图像的图片新闻,这项任务是从图片新闻中选择几个适当的图像作为候选缩略图。为此,我们为此任务提供了一个大型公开的图像数据集,称为图片新闻集合(图片新闻集合0.1版本可以在HTTPS://github.com/Anonymity01/Picture-news-collection上公开提供。) 。图片新闻新闻网站上有超过400万张来自347,731张图片新闻,新闻网站,新浪新闻和网易新闻。选择好的缩略图是复杂的,需要考虑景点,热门话题,内容完整性等的许多方面,以便选择合适的候选缩略图,我们提出了一种基于关注的缩略图选择模型,以及与三个相比的实验结果基于图像分类的基准显示我们所提出的方法优于基线。我们介绍了自动图片新闻缩略图选择任务和数据集,以鼓励进一步研究这一挑战。

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