mlsanityData to 7 Oct 2026

GeoDiffusion: A Training-Free Framework for Accurate 3D Geometric Conditioning in Image Generation

arXiv 2510.22337 ↗First posted 25 Oct 2025cs.CVcited by 2

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Abstract (arXiv)

Precise geometric control in image generation is essential for engineering & product design and creative industries to control 3D object features accurately in image space. Traditional 3D editing approaches are time-consuming and demand specialized skills, while current image-based generative methods lack accuracy in geometric conditioning. To address these challenges, we propose GeoDiffusion, a training-free framework for accurate and efficient geometric conditioning of 3D features in image generation. GeoDiffusion employs a class-specific 3D object as a geometric prior to define keypoints and parametric correlations in 3D space. We ensure viewpoint consistency through a rendered image of a reference 3D object, followed by style transfer to meet user-defined appearance specifications. At the core of our framework is GeoDrag, improving accuracy and speed of drag-based image editing on geometry guidance tasks and general instructions on DragBench. Our results demonstrate that GeoDiffusion enables precise geometric modifications across various iterative design workflows.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 47 of its 51 references that are in the map. First posted on arXiv 25 Oct 2025.

Builds on

47 of 51 references.

References · 47

  1. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  6. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  7. 2020Denoising Diffusion Implicit Modelscited by 9,655
  8. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  9. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  10. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  11. 2023SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesiscited by 4,290
  12. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
35 more
  1. 2022InstructPix2Pix: Learning to Follow Image Editing Instructionscited by 2,591
  2. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  3. 2021CLIPScore: A Reference-free Evaluation Metric for Image Captioningcited by 2,388
  4. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  5. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  6. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
  7. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  8. 2023T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Modelscited by 1,339
  9. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  10. 2022Imagic: Text-Based Real Image Editing with Diffusion Modelscited by 1,172
  11. 2022Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translationcited by 897
  12. 2023Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesiscited by 847
  13. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 834
  14. 2023Zero123++: a Single Image to Consistent Multi-view Diffusion Base Modelcited by 516
  15. 2024SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusioncited by 364
  16. 2021Deep ViT Features as Dense Visual Descriptorscited by 327
  17. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 324
  18. 2023A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondencecited by 297
  19. 2023DragDiffusion: Harnessing Diffusion Models for Interactive Point-based Image Editingcited by 293
  20. 2023Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifoldcited by 218
  21. 2023Diffusion Hyperfeatures: Searching Through Time and Space for Semantic Correspondencecited by 211
  22. 2023DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Modelscited by 193
  23. 2022Sketch-Guided Text-to-Image Diffusion Modelscited by 180
  24. 2022Pretraining is All You Need for Image-to-Image Translationcited by 160
  25. 2024DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editingcited by 88
  26. 2023Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecastingcited by 86
  27. 2023The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editingcited by 61
  28. 2024Drag Your Noise: Interactive Point-based Editing via Diffusion Semantic Propagationcited by 50
  29. 2024Image Sculpting: Precise Object Editing with 3D Geometry Controlcited by 45
  30. 20243DRealCar: An In-the-wild RGB-D Car Dataset with 360-degree Viewscited by 37
  31. 2024DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Predictioncited by 33
  32. 2024GoodDrag: Towards Good Practices for Drag Editing with Diffusion Modelscited by 33
  33. 2023FreeDrag: Feature Dragging for Reliable Point-based Image Editingcited by 28
  34. 2023Generating Images with 3D Annotations Using Diffusion Modelscited by 18
  35. 2024MvDrag3D: Drag-based Creative 3D Editing via Multi-view Generation-Reconstruction Priorscited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 20263DMorph: Single-Image-Guided Local 3D Shape Editing and Morphingcited by 0
  2. 2026SemanticSlider3D: Training-Free Continuous Semantic Editing for 3D Objectscited by 0