Cheapfake is a recently coined term that encompasses non-AI ("cheap") manipulations of multimedia content. Cheapfakes are known to be more prevalent than deepfakes. Cheapfake media can be created using editing software for image/video manipulations, or even without using any software, by simply altering the context of an image/video by sharing the media alongside misleading claims. This alteration of context is referred to as out-of-context (OOC) misuse} of media. OOC media is much harder to detect than fake media, since the images and videos are not tampered. In this challenge, we focus on detecting OOC images, and more specifically the misuse of real photographs with conflicting image captions in news items. The aim of this challenge is to develop and benchmark models that can be used to detect whether given samples (news image and associated captions) are OOC, based on the recently compiled COSMOS dataset.
翻译:Cheapfake 是一个最近发明的术语,它包括了对多媒体内容的非AI(“便宜”)操纵。 Chapfake 已知比深假更普遍。 使用图像/视频操作编辑软件,或者甚至不使用任何软件,可以简单地改变图像/视频的背景,将媒体与误导性主张分享。 这种对背景的改变被称为对媒体的过度使用。 OOC 媒体比假媒体更难探测,因为图像和视频没有被篡改。 在这项挑战中,我们侧重于探测 OOC 图像,更具体地说,是滥用与新闻项目中相矛盾的图像说明的真实照片。 这一挑战的目的是根据最近汇编的COSOMS数据集,制定和基准模型,用以检测特定样本(新图像和相关说明)是否为 OOC 。