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English(EN) DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models

新的DeepFreqMark框架将水印嵌入AI图像

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了DeepFreqMark，一个用于将水印嵌入潜扩散模型（LDMs）生成的AI图像的新颖框架。与之前使用固定模式的方法不同，DeepFreqMark采用了可学习的神经编码器和解码器，以获得更大的容量和灵活性。该系统还引入了基于球形线性插值（Slerp）的攻击模拟，以克服训练瓶颈，实现了更低的比特错误率，并支持高达256比特的消息容量。 AI

影响 该框架通过提供更强大、可扩展的水印解决方案，有助于解决与AI生成图像相关的版权和错误信息问题。

排序理由 该集群描述了一篇新的学术论文，详细介绍了一种用于AI生成图像水印的新颖技术框架。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新的DeepFreqMark框架将水印嵌入AI图像

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该集群描述了一篇新的学术论文，详细介绍了一种用于AI生成图像水印的新颖技术框架。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Chen-Hsiu Huang, Mario K\"oppen, Ja-Ling Wu ·

    DeepFreqMark：用于潜在扩散模型的端到端可学习频域水印，并进行球面攻击模拟

    arXiv:2608.08999v1 Announce Type: cross Abstract: The proliferation of AI-generated images produced by Latent Diffusion Models (LDMs) has raised critical concerns regarding copyright infringement and misinformation. Although existing frequency-domain watermarking methods embed ha…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    DeepFreqMark：用于潜在扩散模型的端到端可学习频域水印，并进行球形攻击模拟

    The proliferation of AI-generated images produced by Latent Diffusion Models (LDMs) has raised critical concerns regarding copyright infringement and misinformation. Although existing frequency-domain watermarking methods embed handcrafted geometric patterns into the initial late…

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