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English(EN) Materialist: Physically Based Editing Using Single-Image Inverse Rendering

Materialist 支持使用单图像进行基于物理的图像编辑

研究人员开发了 Materialist,一个使用单图像逆渲染进行基于物理的图像编辑的新型流程。该方法结合了用于初始材质属性预测的神经网络和用于严格优化的渐进式可微分渲染。Materialist 支持材质编辑、对象插入和重新照明等应用,即使在没有完整场景几何体的情况下也能处理透明度和折射等复杂效果。 AI

影响 引入了一种新的物理一致性图像编辑混合方法,可能提高生成式视觉应用中的真实感。

排序理由 这是一篇详细介绍新图像编辑方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Materialist 支持使用单图像进行基于物理的图像编辑

本文如何被排名

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这是一篇详细介绍新图像编辑方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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Story freshness
126 days old
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完整方法见我们的编辑标准

报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Lezhong Wang, Duc Minh Tran, Ruiqi Cui, Thomson TG, Anders Bjorholm Dahl, Siavash Arjomand Bigdeli, Jeppe Revall Frisvad, Manmohan Chandraker ·

    Materialist:使用单图像逆渲染进行基于物理的编辑

    arXiv:2501.03717v3 Announce Type: replace Abstract: Achieving physically consistent image editing remains a significant challenge in computer vision. Existing image editing methods typically rely on neural networks, which struggle to accurately handle shadows and refractions. Con…