用文本和图像提示精准编辑3D场景，速度快效果真。
GaussEdit: Adaptive 3D Scene Editing with Text and Image Prompts
- 基于3D高斯泼溅，分三阶段实现区域选区与高效编辑
- 在保持全局一致性的前提下完成精细局部修改，提升真实感
- 适合需要高精度定制化3D内容的设计师与开发者
本文提出GaussEdit，一种基于文本和图像提示的自适应3D场景编辑框架。该框架以3D高斯泼溅为场景表示基础，通过三阶段流程实现便捷的感兴趣区域选择与高效编辑。第一阶段初始化3D高斯，确保高质量编辑；第二阶段采用自适应全局-局部优化策略，在保持场景整体一致性的同时实现细节化局部修改，并引入类别引导正则化缓解双重困境（Janus problem）；第三阶段利用先进的图像到图像合成技术增强编辑物体的纹理，使结果视觉逼真且贴合提示。实验表明，GaussEdit在编辑准确性、视觉保真度和处理速度上均优于现有方法。通过成功将用户指定概念嵌入3D场景，GaussEdit成为一种强大的精细化、用户驱动的3D编辑工具，显著优于传统方法。
原文摘要 · Abstract (English)
This paper presents GaussEdit, a framework for adaptive 3D scene editing guided by text and image prompts. GaussEdit leverages 3D Gaussian Splatting as its backbone for scene representation, enabling convenient Region of Interest selection and efficient editing through a three-stage process. The first stage involves initializing the 3D Gaussians to ensure high-quality edits. The second stage employs an Adaptive Global-Local Optimization strategy to balance global scene coherence and detailed local edits and a category-guided regularization technique to alleviate the Janus problem. The final stage enhances the texture of the edited objects using a sophisticated image-to-image synthesis technique, ensuring that the results are visually realistic and align closely with the given prompts. Our experimental results demonstrate that GaussEdit surpasses existing methods in editing accuracy, visual fidelity, and processing speed. By successfully embedding user-specified concepts into 3D scenes, GaussEdit is a powerful tool for detailed and user-driven 3D scene editing, offering significant improvements over traditional methods.
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