mlsanityData to 14 Oct 2026

Hunyuan3D Studio: End-to-End AI Pipeline for Game-Ready 3D Asset Generation

arXiv 2509.12815 ↗First posted 16 Sep 2025cs.CVcited by 13

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Abstract (arXiv)

The creation of high-quality 3D assets, a cornerstone of modern game development, has long been characterized by labor-intensive and specialized workflows. This paper presents Hunyuan3D Studio, an end-to-end AI-powered content creation platform designed to revolutionize the game production pipeline by automating and streamlining the generation of game-ready 3D assets. At its core, Hunyuan3D Studio integrates a suite of advanced neural modules (such as Part-level 3D Generation, Polygon Generation, Semantic UV, etc.) into a cohesive and user-friendly system. This unified framework allows for the rapid transformation of a single concept image or textual description into a fully-realized, production-quality 3D model complete with optimized geometry and high-fidelity PBR textures. We demonstrate that assets generated by Hunyuan3D Studio are not only visually compelling but also adhere to the stringent technical requirements of contemporary game engines, significantly reducing iteration time and lowering the barrier to entry for 3D content creation. By providing a seamless bridge from creative intent to technical asset, Hunyuan3D Studio represents a significant leap forward for AI-assisted workflows in game development and interactive media.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 41 of its 44 references that are in the map. First posted on arXiv 16 Sep 2025.

Builds on

41 of 44 references.

References · 41

  1. 2022Flow Matching for Generative Modelingcited by 5,702
  2. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
  3. 2023Sigmoid Loss for Language Image Pre-Trainingcited by 3,109
  4. 2021Perceiver: General Perception with Iterative Attentioncited by 1,104
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  7. 2015Pointer Networkscited by 895
  8. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 770
  9. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 458
  10. 2024CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assetscited by 455
  11. 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 356
  12. 2024Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understandingcited by 298
29 more
  1. 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 269
  2. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 259
  3. 2023Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representationcited by 228
  4. 2025Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Materialcited by 165
  5. 2025Hunyuan3D 2.5: Towards High-Fidelity 3D Assets Generation with Ultimate Detailscited by 125
  6. 2021Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Biascited by 118
  7. 2024Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scalecited by 89
  8. 2025PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformerscited by 84
  9. 2024Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generationcited by 82
  10. 2024Scaling Mesh Generation via Compressive Tokenizationcited by 73
  11. 2025OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesioncited by 61
  12. 2025HoloPart: Generative 3D Part Amodal Segmentationcited by 60
  13. 2020Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernelscited by 53
  14. 2025Efficient Part-level 3D Object Generation via Dual Volume Packingcited by 48
  15. 2025RigAnything: Template-Free Autoregressive Rigging for Diverse 3D Assetscited by 47
  16. 2025One Model to Rig Them All: Diverse Skeleton Rigging with UniRigcited by 45
  17. 2025X-Part: high fidelity and structure coherent shape decompositioncited by 44
  18. 2025MagicArticulate: Make Your 3D Models Articulation-Readycited by 43
  19. 2025P3-SAM: Native 3D Part Segmentationcited by 43
  20. 2023Nuvo: Neural UV Mapping for Unruly 3D Representationscited by 29
  21. 2025MaterialMVP: Illumination-Invariant Material Generation via Multi-view PBR Diffusioncited by 28
  22. 2025Unleashing Vecset Diffusion Model for Fast Shape Generationcited by 26
  23. 2024Make-It-Animatable: An Efficient Framework for Authoring Animation-Ready 3D Characterscited by 23
  24. 2025Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuningcited by 22
  25. 2025RomanTex: Decoupling 3D-aware Rotary Positional Embedded Multi-Attention Network for Texture Synthesiscited by 20
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  28. 2024Generating 3D House Wireframes with Semanticscited by 8
  29. 2025Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimizationcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 9.

13 papers.

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  1. 2025Hunyuan3D-Omni: A Unified Framework for Controllable Generation of 3D Assetscited by 22
  2. 2025ShapeGen4D: Towards High Quality 4D Shape Generation from Videoscited by 21
  3. 2025MeshMosaic: Scaling Artist Mesh Generation via Local-to-Global Assemblycited by 8
  4. 2025NaTex: Seamless Texture Generation as Latent Color Diffusioncited by 7
  5. 2026HVG-3D: Bridging Real and Simulation Domains for 3D-Conditional Hand-Object Interaction Video Synthesiscited by 7
  6. 2026LottieGPT: Tokenizing Vector Animation for Autoregressive Generationcited by 5
  7. 2026Strips as Tokens: Artist Mesh Generation with Native UV Segmentationcited by 3
  8. 2026AssetGen: Deployable 3D Asset Generation at Interactive Speedcited by 2
  9. 2026Home3D 1.0: A High-Fidelity Image-to-3D Asset Generation System for Interior Designcited by 1
  10. 2026PnP-U3D: Plug-and-Play 3D Framework Bridging Autoregression and Diffusion for Unified Understanding and Generationcited by 0
  11. 2026Hunyuan3D-Buffalo 1.0: A Unified Multimodal Model for Scalable 3D Generation, Understanding, and Editingcited by 0
  12. 2026MultiCube: Compositional 3D Generation With Part-Level Semantic and Spatial Controlcited by 0
1 more
  1. 2026AnimalLift: Reconstructing Animatable 3D Animals from a Single Image by Learning Canonical Shape, Texture, and Fur Mapscited by 0