mlsanityData to 14 Oct 2026

DiverseDream: Diverse Text-to-3D Synthesis with Augmented Text Embedding

arXiv 2312.02192 ↗First posted 2 Dec 2023cs.CVcited by 1

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Abstract (arXiv)

Text-to-3D synthesis has recently emerged as a new approach to sampling 3D models by adopting pretrained text-to-image models as guiding visual priors. An intriguing but underexplored problem with existing text-to-3D methods is that 3D models obtained from the sampling-by-optimization procedure tend to have mode collapses, and hence poor diversity in their results. In this paper, we provide an analysis and identify potential causes of such a limited diversity, which motivates us to devise a new method that considers the joint generation of different 3D models from the same text prompt. We propose to use augmented text prompts via textual inversion of reference images to diversify the joint generation. We show that our method leads to improved diversity in text-to-3D synthesis qualitatively and quantitatively. Project page: https://diversedream.github.io

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 50 of its 63 references that are in the map. First posted on arXiv 2 Dec 2023.

Builds on

50 of 63 references.

References · 50

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2023GPT-4 Technical Reportcited by 18,396
  4. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  5. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  6. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  7. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  8. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  9. 2022DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generationcited by 3,300
  10. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  11. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
  12. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,626
38 more
  1. 2022An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversioncited by 2,245
  2. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
  3. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,489
  4. 2022DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detectioncited by 1,319
  5. 2022Scaling Autoregressive Models for Content-Rich Text-to-Image Generationcited by 1,295
  6. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,290
  7. 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
  8. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,219
  9. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,205
  10. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 964
  11. 2023MVDream: Multi-view Diffusion for 3D Generationcited by 938
  12. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 905
  13. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
  14. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
  15. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 687
  16. 2023Muse: Text-To-Image Generation via Masked Generative Transformerscited by 648
  17. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 560
  18. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  19. 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 511
  20. 2023Scaling up GANs for Text-to-Image Synthesiscited by 492
  21. 2023Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priorscited by 397
  22. 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 385
  23. 2023Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Modelcited by 378
  24. 2021Advances in Neural Renderingcited by 365
  25. 2019SynSin: End-to-end View Synthesis from a Single Imagecited by 364
  26. 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
  27. 2023StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesiscited by 212
  28. 2023Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generationcited by 133
  29. 2023Text-to-3D with Classifier Score Distillationcited by 128
  30. 2023HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidancecited by 110
  31. 2023Noise-Free Score Distillationcited by 99
  32. 2023ATT3D: Amortized Text-to-3D Object Synthesiscited by 87
  33. 2020Improving Image Captioning with Better Use of Captionscited by 84
  34. 2023Consistent123: Improve Consistency for One Image to 3D Object Synthesiscited by 84
  35. 2023DreamTime: An Improved Optimization Strategy for Diffusion-Guided 3D Generationcited by 81
  36. 2023Highly Personalized Text Embedding for Image Manipulation by Stable Diffusioncited by 39
  37. 2021Free-Viewpoint RGB-D Human Performance Capture and Renderingcited by 11
  38. 2023ET3D: Efficient Text-to-3D Generation via Multi-View Distillationcited by 6

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Citing papers per year: 2024: 1.

1 paper.

  1. 2024BrightDreamer: Generic 3D Gaussian Generative Framework for Fast Text-to-3D Synthesiscited by 20