3D editing plays a crucial role in editing and reusing existing 3D assets, thereby enhancing productivity. Recently, 3DGS-based methods have gained increasing attention due to their efficient rendering and flexibility. However, achieving desired 3D editing results often requires multiple adjustments in an iterative loop, resulting in tens of minutes of training time cost for each attempt and a cumbersome trial-and-error cycle for users. This in-the-loop training paradigm results in a poor user experience. To address this issue, we introduce the concept of process-oriented modelling for 3D editing and propose the Progressive Gaussian Differential Field (ProGDF), an out-of-loop training approach that requires only a single training session to provide users with controllable editing capability and variable editing results through a user-friendly interface in real-time. ProGDF consists of two key components: Progressive Gaussian Splatting (PGS) and Gaussian Differential Field (GDF). PGS introduces the progressive constraint to extract the diverse intermediate results of the editing process and employs rendering quality regularization to improve the quality of these results. Based on these intermediate results, GDF leverages a lightweight neural network to model the editing process. Extensive results on two novel applications, namely controllable 3D editing and flexible fine-grained 3D manipulation, demonstrate the effectiveness, practicality and flexibility of the proposed ProGDF.
3D编辑在修改和重用现有3D资产方面起着关键作用，从而显著提升生产效率。近年来，基于3D高斯投影（3D Gaussian Splatting, 3DGS）的方法因其高效渲染和灵活性而备受关注。然而，要实现理想的3D编辑效果，通常需要经过多次调整的迭代循环，每次尝试都可能耗费数十分钟的训练时间，导致用户体验受到冗长试错过程的限制。这种“循环内训练”范式严重降低了用户体验。 为解决这一问题，我们提出了一种面向过程的3D编辑建模新概念，并设计了渐进式高斯差分场（Progressive Gaussian Differential Field, ProGDF），一种“循环外训练”方法。ProGDF仅需一次训练即可通过实时、用户友好的界面为用户提供可控的编辑能力和多样化的编辑结果。 ProGDF由两个关键组件组成：渐进式高斯投影（Progressive Gaussian Splatting, PGS）和高斯差分场（Gaussian Differential Field, GDF）。PGS 引入渐进约束，以提取编辑过程中的多样化中间结果，并通过渲染质量正则化提高这些结果的质量。在此基础上，GDF 利用轻量级神经网络对编辑过程进行建模。 在两种新应用场景——可控3D编辑和灵活的细粒度3D操作——中的广泛实验结果表明，ProGDF 在效果、实用性和灵活性方面表现出显著优势，为3D编辑提供了高效且易用的解决方案。