3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting
Qihang Zhang, Yinghao Xu, Chaoyang Wang, Hsin-Ying Lee, Gordon Wetzstein, Bolei Zhou, Ceyuan Yang
摘要
Scene image editing is crucial for entertainment, photography, and advertising design. Existing methods solely focus on either 2D individual object or 3D global scene editing. This results in a lack of a unified approach to effectively control and manipulate scenes at the 3D level with different levels of granularity. In this work, we propose 3DitScene, a novel and unified scene editing framework leveraging language-guided disentangled Gaussian Splatting that enables seamless editing from 2D to 3D, allowing precise control over scene composition and individual objects. We first incorporate 3D Gaussians that are refined through generative priors and optimization techniques. Language features from CLIP then introduce semantics into 3D geometry for object disentanglement. With the disentangled Gaussians, 3DitScene allows for manipulation at both the global and individual levels, revolutionizing creative expression and empowering control over scenes and objects. Experimental results demonstrate the effectiveness and versatility of 3DitScene in scene image editing.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper13
- SceneDesigner: Controllable Multi-Object Image Generation with 9-DoF Pose ManipulationZhenyuan Qin, Xincheng Shuai, Henghui DingNeurIPS 2025 · 被引用 11 次
- TINKER: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene OptimizationCanyu Zhao, Xiaoman Li, Tianjian Feng, Zhiyue Zhao 等ICLR 2026 · 被引用 9 次
- SeeThrough3D: Occlusion Aware 3D Control in Text-to-Image GenerationVaibhav Agrawal, Rishubh Parihar, Pradhaan Bhat, Ravi Kiran Sarvadevabhatla 等CVPR 2026 · 被引用 5 次
- SonoWorld: From One Image to a 3D Audio-Visual SceneDerong Jin, Xiyi Chen, Ming C. Lin, Ruohan GaoCVPR 2026 · 被引用 4 次
- Zero-Shot Depth Aware Image Editing With Diffusion ModelsRishubh Parihar, Sachidanand VS, R. Venkatesh BabuICCV 2025 · 被引用 3 次
它引用的顶会 Paper41
- Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh 等ICML 2021 · 被引用 47,906 次
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 被引用 35,902 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 被引用 5,687 次
- SDEdit: Guided Image Synthesis and Editing with Stochastic Differential EquationsChenlin Meng, Yutong He, Yang Song, Jiaming Song 等ICLR 2022 · 被引用 2,128 次
相关 Paper
- 3D Gaussian Editing with A Single ImageGuan Luo, Tian-Xing Xu, Ying-Tian Liu, Xiaoxiong Fan 等ACM MM 2024 · 被引用 7 次
- TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-PromptsJingyu Zhuang, Di Kang, Yan-Pei Cao, Guanbin Li 等SIGGRAPH 2024 · 被引用 59 次
- Drag Your Gaussian: Effective Drag-Based Editing with Score Distillation for 3D Gaussian SplattingYansong Qu, Dian Chen, Xinyang Li, Xiaofan Li 等SIGGRAPH 2025 · 被引用 14 次
- GaussianEditor: Editing 3D Gaussians Delicately with Text InstructionsJunjie Wang, Jiemin Fang, Xiaopeng Zhang, Lingxi Xie 等CVPR 2024 · 被引用 65 次
- Edit3D: Elevating 3D Scene Editing with Attention-Driven Multi-Turn InteractivityPeng Zhou, Dunbo Cai, Yujian Du, Runqing Zhang 等ACM MM 2024 · 被引用 3 次
