mlsanityData to 14 Oct 2026

X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation

arXiv 2405.00954 ↗First posted 2 May 2024cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

Recent advancements in automatic 3D avatar generation guided by text have made significant progress. However, existing methods have limitations such as oversaturation and low-quality output. To address these challenges, we propose X-Oscar, a progressive framework for generating high-quality animatable avatars from text prompts. It follows a sequential Geometry->Texture->Animation paradigm, simplifying optimization through step-by-step generation. To tackle oversaturation, we introduce Adaptive Variational Parameter (AVP), representing avatars as an adaptive distribution during training. Additionally, we present Avatar-aware Score Distillation Sampling (ASDS), a novel technique that incorporates avatar-aware noise into rendered images for improved generation quality during optimization. Extensive evaluations confirm the superiority of X-Oscar over existing text-to-3D and text-to-avatar approaches. Our anonymous project page: https://xmu-xiaoma666.github.io/Projects/X-Oscar/.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 58 of its 70 references that are in the map. First posted on arXiv 2 May 2024.

Builds on

58 of 70 references.

References · 58

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  5. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,058
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  7. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  8. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  9. 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generationcited by 4,322
  10. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  11. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  12. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
38 more
  1. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,612
  2. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,290
  3. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,219
  4. 2022Reproducible scaling laws for contrastive language-image learningcited by 1,173
  5. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
  6. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 687
  7. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  8. 2018DensePose: Dense Human Pose Estimation In The Wildcited by 575
  9. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  10. 2022HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Videocited by 483
  11. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 460
  12. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 441
  13. 2023Text-to-3D using Gaussian Splattingcited by 299
  14. 2022CLIP-Mesh: Generating textured meshes from text using pretrained image-text modelscited by 281
  15. 2022X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrievalcited by 280
  16. 2021CLIP-Forge: Towards Zero-Shot Text-to-Shape Generationcited by 254
  17. 2022NeuMan: Neural Human Radiance Field from a Single Videocited by 244
  18. 2022ECON: Explicit Clothed humans Optimized via Normal integrationcited by 199
  19. 2023mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Videocited by 154
  20. 2021imGHUM: Implicit Generative Models of 3D Human Shape and Articulated Posecited by 103
  21. 2023DreamHuman: Animatable 3D Avatars from Textcited by 102
  22. 2023HumanGaussian: Text-Driven 3D Human Generation with Gaussian Splattingcited by 89
  23. 2023HumanNorm: Learning Normal Diffusion Model for High-quality and Realistic 3D Human Generationcited by 88
  24. 2023AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Controlcited by 84
  25. 2023DreamWaltz: Make a Scene with Complex 3D Animatable Avatarscited by 82
  26. 2021Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-Oncited by 81
  27. 2023SIFU: Side-view Conditioned Implicit Function for Real-world Usable Clothed Human Reconstructioncited by 77
  28. 2020Monocular Real-Time Volumetric Performance Capturecited by 74
  29. 2023High-fidelity 3D Human Digitization from Single 2K Resolution Imagescited by 70
  30. 2021DeepMultiCap: Performance Capture of Multiple Characters Using Sparse Multiview Camerascited by 67
  31. 2022SinDDM: A Single Image Denoising Diffusion Modelcited by 60
  32. 2023AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Posecited by 60
  33. 2023Control3D: Towards Controllable Text-to-3D Generationcited by 46
  34. 2023High-Fidelity Clothed Avatar Reconstruction from a Single Imagecited by 38
  35. 2023X-Mesh: Towards Fast and Accurate Text-driven 3D Stylization via Dynamic Textual Guidancecited by 37
  36. 2023AvatarBooth: High-Quality and Customizable 3D Human Avatar Generationcited by 37
  37. 2024HeadStudio: Text to Animatable Head Avatars with 3D Gaussian Splattingcited by 35
  38. 2023GaussianDiffusion: 3D Gaussian Splatting for Denoising Diffusion Probabilistic Models with Structured Noisecited by 30

50 most cited of 58 All 58 (JSON)

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 4.

5 papers.

  1. 2025Compositional Generative Model of Unbounded 4D Citiescited by 17
  2. 2025TeRA: Rethinking Text-guided Realistic 3D Avatar Generationcited by 5
  3. 2024DreamBarbie: Text to Barbie-Style 3D Avatarscited by 4
  4. 2025Text-driven 3D Human Generation via Contrastive Preference Optimizationcited by 1
  5. 2025GaussianIP: Identity-Preserving Realistic 3D Human Generation via Human-Centric Diffusion Priorcited by 0