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arXiv 2407.02411cs.CVcs.CRcs.MM
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视频水印:保护您的视频免受基于视频的大语言模型的(未经授权)标注

Video Watermarking: Safeguarding Your Video from (Unauthorized) Annotations by Video-based LLMs

Tsinghua Shenzhen International Graduate School, Tsinghua University(清华大学深圳国际研究生院);Tencent Technology (Beijing) Co.Ltd(腾讯科技(北京)有限公司);Peng Cheng Laboratory(鹏城实验室)

Jinmin Li, Kuofeng Gao, Yang Bai, Jingyun Zhang, Shu-Tao Xia

AI总结:

本文提出视频水印技术,通过在关键帧中不可察觉地嵌入水印并利用多模态基于流的损失,有效防止基于视频的大语言模型对视频进行未经授权的标注,同时保持观看体验,实验证明其兼具隐蔽性与鲁棒性。

摘要:

基于视频的大语言模型(LLMs)的出现显著增强了视频理解能力。然而,这也引发了一些关于数据保护的安全担忧,因为视频可以更容易地被标注,甚至在未经授权的情况下也是如此。本文介绍了视频水印(Video Watermarking),这是一种新颖的技术,旨在保护视频免受此类基于视频的LLMs的未经授权标注,特别是在响应特定查询时涉及视频内容和描述的情况。通过在关键视频帧中难以察觉地嵌入水印,并采用多模态基于流的损失,我们的方法在保持观看体验的同时,防止了基于视频的LLMs的滥用。大量实验表明,视频水印显著降低了各种基于视频的LLMs对视频的可理解性,展示了其隐蔽性和鲁棒性。本质上,我们的方法为保护视频内容提供了一种解决方案,在面对不断发展的基于视频的LLMs技术时,确保其完整性和机密性。

英文摘要:

The advent of video-based Large Language Models (LLMs) has significantly enhanced video understanding. However, it has also raised some safety concerns regarding data protection, as videos can be more easily annotated, even without authorization. This paper introduces Video Watermarking, a novel technique to protect videos from unauthorized annotations by such video-based LLMs, especially concerning the video content and description, in response to specific queries. By imperceptibly embedding watermarks into key video frames with multi-modal flow-based losses, our method preserves the viewing experience while preventing misuse by video-based LLMs. Extensive experiments show that Video Watermarking significantly reduces the comprehensibility of videos with various video-based LLMs, demonstrating both stealth and robustness. In essence, our method provides a solution for securing video content, ensuring its integrity and confidentiality in the face of evolving video-based LLMs technologies.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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