An Efficient and Effective Watermarking Scheme for the Protection of the Intellectual Property Rights of Video Generative Models

2026-09-20

AI Summary

本文提出一种基于VidMark网络的视频水印方案，通过两尺度离散小波变换和全局时间注意力块增强水印鲁棒性和不可感知性，解决合成视频验证和模型所有权验证问题。

Abstract

The rapid development of video generative models (VGMs) has enabled the generation of highly realistic synthetic videos, raising concerns about the intellectual property rights (IPR) of these models. In particular, two closely related forensic tasks remain largely unaddressed: synthetic video verification (determining whether a video was generated by a protected VGM) and model ownership verification (determining whether a suspect VGM is an unauthorized copy of a protected VGM). In this paper, we propose a new in-generation watermarking scheme that can address the two verification tasks. First, a novel video watermarking network named VidMark is presented, which incorporates a two-scale discrete wavelet transform (DWT) decomposition and a global temporal attention block (GTAB) to enhance watermark robustness and imperceptibility. Second, we present a decoder-guided fine-tuning procedure. By leveraging the frozen VidMark decoder, this process enables VGMs to synthesize videos carrying an imperceptible, robust, and model-specific watermark. Finally, two verification frameworks are established to perform synthetic video verification and model ownership verification. Extensive experiments on representative VGMs demonstrate that the proposed scheme achieves over 99% watermark extraction accuracy and 100% verification accuracy on both tasks, with negligible impact on video generation quality. Furthermore, the watermarks exhibit strong robustness against a comprehensive range of video-level and model-level attacks.

Problem

• Video Generative Models
• Intellectual Property Rights
• Synthetic Video Verification
• Model Ownership Verification

Innovation

• VidMark
• discrete wavelet transform (DWT)
• global temporal attention block (GTAB)
• decoder-guided fine-tuning