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.

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MMSys'21 检测廉价假货的大挑战

廉价假货是最近创造的术语，它包含对多媒体内容的非 AI（“廉价”）操作。众所周知，Cheapfakes 比 deepfakes 更普遍。可以使用用于图像/视频操作的编辑软件来创建廉价媒体，甚至可以不使用任何软件，通过与误导性声明一起共享媒体来简单地更改图像/视频的上下文。这种上下文的改变被称为媒体的上下文外 (OOC) 滥用}。OOC 媒体比假媒体更难检测，因为图像和视频没有被篡改。在这个挑战中，我们专注于检测 OOC 图像，更具体地说，是在新闻项目中误用带有冲突图像标题的真实照片。