Text-driven 3D editing enables user-friendly 3D object or scene editing with text instructions. Due to the lack of multi-view consistency priors, existing methods typically resort to employing 2D generation or editing models to process each view individually, followed by iterative 2D-3D-2D updating. However, these methods are not only time-consuming but also prone to over-smoothed results because the different editing signals gathered from different views are averaged during the iterative process. In this paper, we propose generative Video Prior based 3D Editing (ViP3DE) to employ the temporal consistency priors from pre-trained video generation models for multi-view consistent 3D editing in a single forward pass. Our key insight is to condition the video generation model on a single edited view to generate other consistent edited views for 3D updating directly, thereby bypassing the iterative editing paradigm. Since 3D updating requires edited views to be paired with specific camera poses, we propose motion-preserved noise blending for the video model to generate edited views at predefined camera poses. In addition, we introduce geometry-aware denoising to further enhance multi-view consistency by integrating 3D geometric priors into video models. Extensive experiments demonstrate that our proposed ViP3DE can achieve high-quality 3D editing results even within a single forward pass, significantly outperforming existing methods in both editing quality and speed.

翻译：文本驱动的三维编辑允许用户通过文本指令便捷地编辑三维物体或场景。由于缺乏多视角一致性先验，现有方法通常采用二维生成或编辑模型分别处理每个视角，随后进行迭代式的二维-三维-二维更新。然而，这些方法不仅耗时，且容易因迭代过程中不同视角的编辑信号被平均化而导致结果过度平滑。本文提出基于生成式视频先验的三维编辑方法（ViP3DE），利用预训练视频生成模型中的时序一致性先验，通过单次前向传播实现多视角一致的三维编辑。我们的核心思路是：以单个编辑后的视角为条件，驱动视频生成模型直接生成其他具有一致性的编辑视角，用于三维更新，从而绕过迭代编辑范式。由于三维更新需要编辑后的视角与特定相机位姿配对，我们提出运动保持噪声融合技术，使视频模型能在预设相机位姿下生成编辑视角。此外，我们引入几何感知去噪方法，通过将三维几何先验整合到视频模型中，进一步提升多视角一致性。大量实验表明，即使仅通过单次前向传播，我们提出的ViP3DE仍能实现高质量的三维编辑效果，在编辑质量和速度上均显著优于现有方法。