mlsanityData to 7 Oct 2026

TextMesh: Generation of Realistic 3D Meshes From Text Prompts

arXiv 2304.12439 ↗First posted 24 Apr 2023cs.CVcited by 135

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

Abstract (arXiv)

The ability to generate highly realistic 2D images from mere text prompts has recently made huge progress in terms of speed and quality, thanks to the advent of image diffusion models. Naturally, the question arises if this can be also achieved in the generation of 3D content from such text prompts. To this end, a new line of methods recently emerged trying to harness diffusion models, trained on 2D images, for supervision of 3D model generation using view dependent prompts. While achieving impressive results, these methods, however, have two major drawbacks. First, rather than commonly used 3D meshes, they instead generate neural radiance fields (NeRFs), making them impractical for most real applications. Second, these approaches tend to produce over-saturated models, giving the output a cartoonish looking effect. Therefore, in this work we propose a novel method for generation of highly realistic-looking 3D meshes. To this end, we extend NeRF to employ an SDF backbone, leading to improved 3D mesh extraction. In addition, we propose a novel way to finetune the mesh texture, removing the effect of high saturation and improving the details of the output 3D mesh.

Key facts. Cited by 135 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 26 of its 38 references that are in the map. First posted on arXiv 24 Apr 2023.

Builds on

26 of 38 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022Magic3D: High-Resolution Text-to-3D Content Creation18 Nov
  2. 2022DreamFusion: Text-to-3D using 2D Diffusion29 Sep

Other references · 24

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  4. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  5. 2022Classifier-Free Diffusion Guidancecited by 5,717
  6. 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
  7. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  8. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  9. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,287
  10. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  11. 2021Volume Rendering of Neural Implicit Surfacescited by 990
  12. 2022eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoiserscited by 921
12 more
  1. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 699
  2. 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 643
  3. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 640
  4. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  5. 2022Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priorscited by 487
  6. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
  7. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  8. 2021Text2Mesh: Text-Driven Neural Stylization for Meshescited by 332
  9. 2022CLIP-Mesh: Generating textured meshes from text using pretrained image-text modelscited by 281
  10. 2022The Role of ImageNet Classes in Fr'echet Inception Distancecited by 211
  11. 2023Delicate Textured Mesh Recovery from NeRF via Adaptive Surface Refinementcited by 106
  12. 2021MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Imagescited by 78

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 49; 2024: 58; 2025: 23; 2026: 5.

135 papers.

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  1. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
  2. 2023MVDream: Multi-view Diffusion for 3D Generationcited by 928
  3. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 837
  4. 2024LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creationcited by 730
  5. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 682
  6. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 638
  7. 2023ImageDream: Image-Prompt Multi-view Diffusion for 3D Generationcited by 256
  8. 2023GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Modelscited by 255
  9. 2024CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Modelcited by 214
  10. 2023Scalable 3D Captioning with Pretrained Modelscited by 201
  11. 2023Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Modelscited by 169
  12. 2023RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3Dcited by 168
38 more
  1. 2023SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3Dcited by 134
  2. 2023Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Modelscited by 122
  3. 2024RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPScited by 110
  4. 2023Noise-Free Score Distillationcited by 99
  5. 2024Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attentioncited by 99
  6. 2023Text-Guided Texturing by Synchronized Multi-View Diffusioncited by 86
  7. 2023A Unified Approach for Text- and Image-guided 4D Scene Generationcited by 82
  8. 2023DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generationcited by 81
  9. 2023FocalDreamer: Text-driven 3D Editing via Focal-fusion Assemblycited by 75
  10. 2023EpiDiff: Enhancing Multi-View Synthesis via Localized Epipolar-Constrained Diffusioncited by 72
  11. 20243DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priorscited by 72
  12. 2023GPT4Point: A Unified Framework for Point-Language Understanding and Generationcited by 69
  13. 2024SPAD : Spatially Aware Multiview Diffuserscited by 62
  14. 2023Generative AI meets 3D: A Survey on Text-to-3D in AIGC Eracited by 61
  15. 2023Gaussian Shell Maps for Efficient 3D Human Generationcited by 61
  16. 2024ViewDiff: 3D-Consistent Image Generation with Text-to-Image Modelscited by 57
  17. 2023T3Bench: Benchmarking Current Progress in Text-to-3D Generationcited by 56
  18. 2023Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Promptscited by 51
  19. 2023HeadSculpt: Crafting 3D Head Avatars with Textcited by 48
  20. 2023Instant3D: Instant Text-to-3D Generationcited by 45
  21. 2024Efficient4D: Fast Dynamic 3D Object Generation from a Single-view Videocited by 44
  22. 2024DressCode: Autoregressively Sewing and Generating Garments from Text Guidancecited by 43
  23. 2024Instant3dit: Multiview Inpainting for Fast Editing of 3D Objectscited by 43
  24. 2023Alchemist: Parametric Control of Material Properties with Diffusion Modelscited by 38
  25. 2024Rethinking Score Distillation as a Bridge Between Image Distributionscited by 36
  26. 2023Taming Mode Collapse in Score Distillation for Text-to-3D Generationcited by 35
  27. 2024LLMs Meet Multimodal Generation and Editing: A Surveycited by 35
  28. 20233D Paintbrush: Local Stylization of 3D Shapes with Cascaded Score Distillationcited by 34
  29. 2023Disentangled Clothed Avatar Generation from Text Descriptionscited by 33
  30. 2023GaussianDiffusion: 3D Gaussian Splatting for Denoising Diffusion Probabilistic Models with Structured Noisecited by 30
  31. 2024DreamMotion: Space-Time Self-Similar Score Distillation for Zero-Shot Video Editingcited by 28
  32. 2024ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillationcited by 27
  33. 2024DreamFlow: High-Quality Text-to-3D Generation by Approximating Probability Flowcited by 26
  34. 2023Repaint123: Fast and High-quality One Image to 3D Generation with Progressive Controllable 2D Repaintingcited by 25
  35. 2023Collaborative Score Distillation for Consistent Visual Synthesiscited by 23
  36. 2023SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identitycited by 23
  37. 2024HexaGen3D: StableDiffusion is just one step away from Fast and Diverse Text-to-3D Generationcited by 21
  38. 2023DreamPropeller: Supercharge Text-to-3D Generation with Parallel Samplingcited by 20

50 most cited of 135 All 135 (JSON)

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  1. 2023Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields
  2. 2022Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models
  3. 2024DreamMesh: Jointly Manipulating and Texturing Triangle Meshes for Text-to-3D Generation
  4. 2023Guide3D: Create 3D Avatars from Text and Image Guidance
  5. 2023PI3D: Efficient Text-to-3D Generation with Pseudo-Image Diffusion
  6. 2023Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
  7. 2024VP3D: Unleashing 2D Visual Prompt for Text-to-3D Generation
  8. 2025Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Data