mlsanityData to 7 Oct 2026

ControlDreamer: Blending Geometry and Style in Text-to-3D

arXiv 2312.01129 ↗First posted 2 Dec 2023cs.CVcited by 3

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Abstract (arXiv)

Recent advancements in text-to-3D generation have significantly contributed to the automation and democratization of 3D content creation. Building upon these developments, we aim to address the limitations of current methods in blending geometries and styles in text-to-3D generation. We introduce multi-view ControlNet, a novel depth-aware multi-view diffusion model trained on generated datasets from a carefully curated text corpus. Our multi-view ControlNet is then integrated into our two-stage pipeline, ControlDreamer, enabling text-guided generation of stylized 3D models. Additionally, we present a comprehensive benchmark for 3D style editing, encompassing a broad range of subjects, including objects, animals, and characters, to further facilitate research on diverse 3D generation. Our comparative analysis reveals that this new pipeline outperforms existing text-to-3D methods as evidenced by human evaluations and CLIP score metrics. Project page: https://controldreamer.github.io

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 33 of its 44 references that are in the map. First posted on arXiv 2 Dec 2023.

Builds on

33 of 44 references.

References · 33

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  12. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
21 more
  1. 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
  2. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  3. 2019Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfercited by 1,484
  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
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  7. 2021Variational Diffusion Modelscited by 1,145
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  9. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
  10. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 684
  11. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  12. 2023Instruct-NeRF2NeRF: Editing 3D Scenes with Instructionscited by 482
  13. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
  14. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
  15. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  16. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 303
  17. 2023Text2Tex: Text-driven Texture Synthesis via Diffusion Modelscited by 234
  18. 2017Parallel WaveNet: Fast High-Fidelity Speech Synthesiscited by 214
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025CMD: Controllable Multiview Diffusion for 3D Editing and Progressive Generationcited by 14
  2. 2026Deep Sketch-Based 3D Modeling: A Surveycited by 3
  3. 2025GuideFlow3D: Optimization-Guided Rectified Flow For Appearance Transfercited by 2

Similar, not cited

Close in wording, no citation either way

  1. 2024SketchDream: Sketch-based Text-to-3D Generation and Editing
  2. 2023Control3D: Towards Controllable Text-to-3D Generation
  3. 2026DreamEdit3D: Personalization of Multi-View Diffusion Models for 3D Editing
  4. 2024A Survey On Text-to-3D Contents Generation In The Wild
  5. 2023MetaDreamer: Efficient Text-to-3D Creation With Disentangling Geometry and Texture
  6. 2024Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation
  7. 2025Make Your MoVe: Make Your 3D Contents by Adapting Multi-View Diffusion Models to External Editing
  8. 2023EfficientDreamer: High-Fidelity and Robust 3D Creation via Orthogonal-view Diffusion Prior