MFC数据集:媒体取证挑战评估的大规模基准数据集

Haiying Guan, Mark Kozak, Eric Robertson, Yooyoung Lee, Amy N. Yates, Andrew Delgado, Daniel Zhou, Timothée Kheyrkhah, Jeff M. Smith, J. Fiscus
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引用次数: 128

摘要

我们为数字媒体取证挑战(MFC)评估提供了一个基准。我们的综合数据包括超过176,000张高来源(HP)图像和11,000个HP视频;10万多张篡改图像和4000多段篡改视频;3500万张网络图片和30万段视频。我们设计并生成了一系列的开发、评估和挑战数据集,并使用它们来评估进展,并在过去两年中彻底分析了不同系统在各种媒体取证任务中的性能。在本文中,我们首先介绍了构建媒体取证评估数据集的目标、挑战和方法。然后,我们讨论了取证数据集收集、注释和操作的方法,并提出了有效构建评估数据集的设计和基础设施,以支持各种评估任务。给定一个指定的查询,我们构建一个基础设施,为目标分析报告选择自定义的评估子集。最后,对以往的评价结果进行了论证。
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MFC Datasets: Large-Scale Benchmark Datasets for Media Forensic Challenge Evaluation
We provide a benchmark for digital Media Forensics Challenge (MFC) evaluations. Our comprehensive data comprises over 176,000 high provenance (HP) images and 11,000 HP videos; more than 100,000 manipulated images and 4,000 manipulated videos; 35 million internet images and 300,000 video clips. We have designed and generated a series of development, evaluation, and challenge datasets, and used them to assess the progress and thoroughly analyze the performance of diverse systems on a variety of media forensics tasks in the past two years. In this paper, we first introduce the objectives, challenges, and approaches to building media forensics evaluation datasets. We then discuss our approaches to forensic dataset collection, annotation, and manipulation, and present the design and infrastructure to effectively and efficiently build the evaluation datasets to support various evaluation tasks. Given a specified query, we build an infrastructure that selects the customized evaluation subsets for the targeted analysis report. Finally, we demonstrate the evaluation results in the past evaluations.
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