English(EN) Depth-to-RGB: Repurposing a Frozen Depth Estimator for Geometry-Guided Compositing

Depth-to-RGB框架通过预测深度增强场景合成

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-08 04:00

研究人员开发了一个名为Depth-to-RGB (D2R)的新框架，该框架通过在场景渲染为RGB之前预测场景的深度来增强对象合成。该方法通过学习参考条件校正来重新利用冻结的深度估计器，然后用于指导RGB渲染器。与现有基线相比，D2R框架显著提高了几何精度和光度质量，并在各种基准测试中展示了强大的泛化能力。 AI

影响这项研究可能在从图形设计到虚拟环境的各种应用中实现更真实、几何一致的图像合成。

排序理由详细介绍新技术框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Sanghyun Jo, Chae Yeon Lim, Donghwan Lee, Sihyun Kim, Soo Ye Kim, Kyungsu Kim · 2026-10-08 04:00

Depth-to-RGB：重新利用冻结的深度估计器进行几何引导的合成

arXiv:2610.09125v1 Announce Type: new Abstract: Reference-based object compositing inserts or replaces an object using a background image, a reference image, and a 2D compositing mask. These inputs guide appearance and placement but leave the completed scene's geometry implicit, …

本文如何被排名

报道来源 [1]

Depth-to-RGB：重新利用冻结的深度估计器进行几何引导的合成

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