ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing
Jun-Kun Chen, Yu-Xiong Wang
Abstract
This paper proposes ProEdit - a simple yet effective framework for high-quality 3D scene editing guided by diffusion distillation in a novel progressive manner. Inspired by the crucial observation that multi-view inconsistency in scene editing is rooted in the diffusion model's large feasible output space (FOS), our framework controls the size of FOS and reduces inconsistency by decomposing the overall editing task into several subtasks, which are then executed progressively on the scene. Within this framework, we design a difficulty-aware subtask decomposition scheduler and an adaptive 3D Gaussian splatting (3DGS) training strategy, ensuring high quality and efficiency in performing each subtask. Extensive evaluation shows that our ProEdit achieves state-of-the-art results in various scenes and challenging editing tasks, all through a simple framework without any expensive or sophisticated add-ons like distillation losses, components, or training procedures. Notably, ProEdit also provides a new way to control, preview, and select the"aggressivity"of editing operation during the editing process.
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Cited by top-tier papers5
- 3D-LATTE: Latent Space 3D Editing from Textual InstructionsMaria Parelli, Michael Oechsle, Michael Niemeyer, Federico Tombari et al.CVPR 2026 · 10 citations
- InterGSEdit: Interactive 3D Gaussian Splatting Editing with 3D Geometry-Consistent Attention PriorMinghao Wen, Shengjie Wu, Kangkan Wang, Dong LiangICCV 2025 · 5 citations
- DEGauss: Defending Against Malicious 3D Editing for Gaussian SplattingLingzhuang Meng, Mingwen Shao, Yuanjian Qiao, Xiang LvNeurIPS 2025 · 4 citations
- Variation-aware Flexible 3D Gaussian EditingHao Qin, Yukai Sun, Meng Wang, Ming Kong et al.ICLR 2026 · 3 citations
- 3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D EditingJiahua Dong, Yu-Xiong WangICLR 2025
Builds on27
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 5,687 citations
- SDEdit: Guided Image Synthesis and Editing with Stochastic Differential EquationsChenlin Meng, Yutong He, Yang Song, Jiaming Song et al.ICLR 2022 · 2,128 citations
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