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

机译:图片新闻收藏:自动选择图片新闻缩略图的数据集

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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:近年来,图片新闻在在线新闻中变得越来越流行。作为对观众的第一印象,缩略图在图片新闻中起着非常重要的作用。但是,手动选择缩略图以获取大量图片新闻非常耗时。在本文中,我们介绍了自动图片新闻缩略图选择的新任务。给定一条包含一组图像的图片新闻,此任务是从该图片新闻中选择几个合适的图像作为候选缩略图。为此,我们为该任务提供了一个大型的公开可用图像数据集,称为图片新闻集(图片新闻集0.1版可以在https://github.com/anonymity01/Picture-News-Collection上在线公开获得。) 。图片新闻集包含来自两个著名新闻网站新浪新闻和网易新闻的347,731张图片新闻的超过400万张图片。选择足够好的缩略图非常复杂,需要考虑很多方面,例如吸引力,热门话题,内容完整性等。为了选择合适的候选缩略图,我们提出了一种基于注意力的缩略图选择模型,并将实验结果与三种方法进行比较基于图像分类的基线表明,我们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,以鼓励对此挑战进行进一步研究。

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