mlsanityData to 7 Oct 2026

iControl3D: An Interactive System for Controllable 3D Scene Generation

arXiv 2408.01678 ↗First posted 3 Aug 2024cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D object and scene generation, they still fall short of providing sufficient control over the generation process, leading to a gap between the user's creative vision and the generated results. In this paper, we present iControl3D, a novel interactive system that empowers users to generate and render customizable 3D scenes with precise control. To this end, a 3D creator interface has been developed to provide users with fine-grained control over the creation process. Technically, we leverage 3D meshes as an intermediary proxy to iteratively merge individual 2D diffusion-generated images into a cohesive and unified 3D scene representation. To ensure seamless integration of 3D meshes, we propose to perform boundary-aware depth alignment before fusing the newly generated mesh with the existing one in 3D space. Additionally, to effectively manage depth discrepancies between remote content and foreground, we propose to model remote content separately with an environment map instead of 3D meshes. Finally, our neural rendering interface enables users to build a radiance field of their scene online and navigate the entire scene. Extensive experiments have been conducted to demonstrate the effectiveness of our system. The code will be made available at https://github.com/xingyi-li/iControl3D.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 37 of its 56 references that are in the map. First posted on arXiv 3 Aug 2024.

Builds on

37 of 56 references.

References · 37

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  3. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  4. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  5. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  6. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  7. 2016Improved Techniques for Training GANscited by 2,938
  8. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
  9. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
  10. 2020GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fieldscited by 784
  11. 2020Accelerating 3D Deep Learning with PyTorch3Dcited by 781
  12. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
25 more
  1. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  2. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 596
  3. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
  4. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  5. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  6. 2019SynSin: End-to-end View Synthesis from a Single Imagecited by 364
  7. 2023Generative Novel View Synthesis with 3D-Aware Diffusion Modelscited by 273
  8. 2020Learning Gradient Fields for Shape Generationcited by 245
  9. 2020Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Imagecited by 239
  10. 2018Stereo Magnification: Learning View Synthesis using Multiplane Imagescited by 206
  11. 20203D Photography using Context-aware Layered Depth Inpaintingcited by 206
  12. 2018Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddingscited by 169
  13. 2023SceneScape: Text-Driven Consistent Scene Generationcited by 160
  14. 2022GAUDI: A Neural Architect for Immersive 3D Scene Generationcited by 136
  15. 2021Unconstrained Scene Generation with Locally Conditioned Radiance Fieldscited by 130
  16. 2021Pathdreamer: A World Model for Indoor Navigationcited by 117
  17. 2023Consistent View Synthesis with Pose-Guided Diffusion Modelscited by 117
  18. 2021PixelSynth: Generating a 3D-Consistent Experience from a Single Imagecited by 82
  19. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  20. 2023SceneDreamer: Unbounded 3D Scene Generation from 2D Image Collectionscited by 72
  21. 2022Understanding Pure CLIP Guidance for Voxel Grid NeRF Modelscited by 56
  22. 2022Look Outside the Room: Synthesizing A Consistent Long-Term 3D Scene Video from A Single Imagecited by 55
  23. 2021SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpaintingcited by 48
  24. 2023Persistent Nature: A Generative Model of Unbounded 3D Worldscited by 44
  25. 2022Text2Light: Zero-Shot Text-Driven HDR Panorama Generationcited by 24

Built on by

Cited by year (2026 to 7 Oct)

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

2 papers.