mlsanityData to 7 Oct 2026

C3Editor: Achieving Controllable Consistency in 2D Model for 3D Editing

arXiv 2510.04539 ↗First posted 6 Oct 2025cs.GR cs.CVcited by 4

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Abstract (arXiv)

Existing 2D-lifting-based 3D editing methods often encounter challenges related to inconsistency, stemming from the lack of view-consistent 2D editing models and the difficulty of ensuring consistent editing across multiple views. To address these issues, we propose C3Editor, a controllable and consistent 2D-lifting-based 3D editing framework. Given an original 3D representation and a text-based editing prompt, our method selectively establishes a view-consistent 2D editing model to achieve superior 3D editing results. The process begins with the controlled selection of a ground truth (GT) view and its corresponding edited image as the optimization target, allowing for user-defined manual edits. Next, we fine-tune the 2D editing model within the GT view and across multiple views to align with the GT-edited image while ensuring multi-view consistency. To meet the distinct requirements of GT view fitting and multi-view consistency, we introduce separate LoRA modules for targeted fine-tuning. Our approach delivers more consistent and controllable 2D and 3D editing results than existing 2D-lifting-based methods, outperforming them in both qualitative and quantitative evaluations.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 41 of its 46 references that are in the map. First posted on arXiv 6 Oct 2025.

Builds on

41 of 46 references.

References · 41

  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. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  5. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  6. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  7. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  8. 2019Parameter-Efficient Transfer Learning for NLPcited by 4,195
  9. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,878
  10. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  11. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  12. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
29 more
  1. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  2. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  3. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
  4. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
  5. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
  6. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  7. 2022Multi-Concept Customization of Text-to-Image Diffusioncited by 1,099
  8. 2023MVDream: Multi-view Diffusion for 3D Generationcited by 928
  9. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
  10. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 696
  11. 2021P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Taskscited by 686
  12. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 684
  13. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
  14. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  15. 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 482
  16. 2022Blended Latent Diffusioncited by 430
  17. 2023Universal Guidance for Diffusion Modelscited by 426
  18. 2023GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splattingcited by 331
  19. 2024DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editingcited by 92
  20. 2024ViCA-NeRF: View-Consistency-Aware 3D Editing of Neural Radiance Fieldscited by 68
  21. 2023Prompt-Free Diffusion: Taking "Text" out of Text-to-Image Diffusion Modelscited by 62
  22. 2023The Chosen One: Consistent Characters in Text-to-Image Diffusion Modelscited by 62
  23. 2024MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editingcited by 30
  24. 2025DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusioncited by 23
  25. 2024Bayesian Diffusion Models for 3D Shape Reconstructioncited by 19
  26. 2024ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editingcited by 18
  27. 2024ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editingcited by 12
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  29. 2025Lay-Your-Scene: Natural Scene Layout Generation with Diffusion Transformerscited by 6

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.

  1. 2026Omni-3DEdit: Generalized Versatile 3D Editing in One-Passcited by 6
  2. 2025InstructMix2Mix: Consistent Sparse-View Editing Through Multi-View Model Personalizationcited by 1
  3. 20253D-Consistent Multi-View Editing by Correspondence Guidancecited by 1
  4. 2025Gaussian Swaying: Surface-Based Framework for Aerodynamic Simulation with 3D Gaussianscited by 0