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,它包括了非AI(“cheap'”)对多媒体内容的操纵。 Chapfake 已知比深假更普遍。 廉价fake 媒体可以使用编辑软件为图像/视频操作创建, 或甚至不使用任何软件, 简单地改变图像/ 视频的背景, 分享媒体和误导性主张。 这种背景改变被称为媒体的过度使用。 OOC 媒体比假媒体更难被发现, 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, 更具体地说就是滥用与新闻项目图像描述相矛盾的真实照片。 这一挑战的目的是制定和基准模型, 用来检测特定样本( 新图像和相关字幕) 是否为 OOC, 依据最近汇编的 COSMOS 数据集 。