mlsanityData to 7 Oct 2026

ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing

arXiv 2411.05006 ↗First posted 7 Nov 2024cs.CVcited by 12

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 42 of its 49 references that are in the map. First posted on arXiv 7 Nov 2024.

Builds on

42 of 49 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editing13 Jun
  2. 2024Instruct 4D-to-4D: Editing 4D Scenes as Pseudo-3D Scenes Using 2D Diffusion13 Jun
  3. 2023Efficient-NeRF2NeRF: Streamlining Text-Driven 3D Editing with Multiview Correspondence-Enhanced Diffusion Models13 Dec
  4. 2023Edit-DiffNeRF: Editing 3D Neural Radiance Fields using 2D Diffusion Model15 Jun
  5. 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep

Other references · 37

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  5. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  6. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  7. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  8. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  9. 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,144
  10. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
  11. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  12. 2020Neural Sparse Voxel Fieldscited by 959
25 more
  1. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 904
  2. 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 753
  3. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  4. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 596
  5. 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 482
  6. 2024Evaluating Text-to-Visual Generation with Image-to-Text Generationcited by 465
  7. 2022Decomposing NeRF for Editing via Feature Field Distillationcited by 370
  8. 2023GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splattingcited by 331
  9. 2021Learning Object-Compositional Neural Radiance Field for Editable Scene Renderingcited by 228
  10. 2021Editing Conditional Radiance Fieldscited by 222
  11. 2023Gaussian-Flow: 4D Reconstruction with Dynamic 3D Gaussian Particlecited by 210
  12. 2015Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fieldscited by 169
  13. 2023DreamEditor: Text-Driven 3D Scene Editing with Neural Fieldscited by 154
  14. 2024DN-Splatter: Depth and Normal Priors for Gaussian Splatting and Meshingcited by 136
  15. 2017SurfaceNet: An End-to-end 3D Neural Network for Multiview Stereopsiscited by 128
  16. 2021NeRFReN: Neural Radiance Fields with Reflectionscited by 121
  17. 2021NeRF for Outdoor Scene Relightingcited by 114
  18. 20243DGSR: Implicit Surface Reconstruction with 3D Gaussian Splattingcited by 78
  19. 2024ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fieldscited by 68
  20. 2023ConsistNet: Enforcing 3D Consistency for Multi-view Images Diffusioncited by 65
  21. 2021DIVeR: Real-time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Renderingcited by 60
  22. 2022NeuPhysics: Editable Neural Geometry and Physics from Monocular Videoscited by 50
  23. 2023Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversioncited by 47
  24. 2023Posterior Distillation Samplingcited by 45
  25. 2023NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Cloudscited by 41

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 8; 2026: 2.

12 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2024EditSplat: Multi-View Fusion and Attention-Guided Optimization for View-Consistent 3D Scene Editing with 3D Gaussian Splatting
  2. 2025DisCo3D: Distilling Multi-View Consistency for 3D Scene Editing
  3. 2024Towards a Training Free Approach for 3D Scene Editing
  4. 2025Tinker: Diffusion's Gift to 3D--Multi-View Consistent Editing From Sparse Inputs without Per-Scene Optimization
  5. 2024DreamCatalyst: Fast and High-Quality 3D Editing via Controlling Editability and Identity Preservation
  6. 2024Diffusion-Based Attention Warping for Consistent 3D Scene Editing
  7. 2026Look Before You Edit: Attention-Guided Camera Placement and Multi-View Alignment for 3D Gaussian Splatting Editing
  8. 2025Edit2Perceive: Image Editing Diffusion Models Are Strong Dense Perceivers