Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation
On the map: Diffusion models → 3D, point cloud and scene generation
Abstract (arXiv)
Autoregressive (AR) modeling has recently achieved remarkable progress in native 3D mesh generation, largely due to its natural ability to handle variable-length, discrete data structures. However, the inherent constraints of the AR paradigm severely restrict the generated meshes, leading to limited face counts, bounded vertex resolutions, and difficulties in supporting textures. To overcome these bottlenecks, we propose the Barycentric Dominance Field (BDF), a continuous representation defined on triangular mesh surfaces that elegantly encodes vertex topological connectivity. BDF bridges the fundamental gap between discrete mesh topology and continuous diffusion-based generative modeling by transforming connectivity into a continuous surface signal. As an intrinsic mesh property, BDF shares strong similarities with texture maps, enabling its seamless integration into existing 3D diffusion pipelines without requiring architectural modifications. Extensive experiments demonstrate that BDF empowers diffusion models to generate native meshes with significantly higher quality, greater scalability, and stronger robustness compared to state-of-the-art autoregressive methods.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 32 of its 37 references that are in the map. First posted on arXiv 30 Jun 2026.
Builds on
32 of 37 references.
Closest ancestors · 11
Same direction, newest first
- 2026LATO: 3D Mesh Flow Matching with Structured TOpology Preserving LAtents6 Mar
- 2025PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion24 Nov
- 2025Sparc3D: Sparse Representation and Construction for High-Resolution 3D Shapes Modeling20 May
- 2025MeshCraft: Exploring Efficient and Controllable Mesh Generation with Flow-based DiTs29 Mar
- 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation21 Jan
- 2024Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation4 Nov
- 2024CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assets30 May
- 2024Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer23 May
- 2023PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models18 Dec
- 2022Point-E: A System for Generating 3D Point Clouds from Complex Prompts16 Dec
- 2022Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion12 Dec
Other references · 21
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
- 2022Scalable Diffusion Models with Transformerscited by 6,054
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
- 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 385
- 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 269
- 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 259
- 2025Native and Compact Structured Latents for 3D Generationcited by 175
- 2023Flexible Isosurface Extraction for Gradient-Based Mesh Optimizationcited by 139
- 2021Using Shape to Categorize: Low-Shot Learning with an Explicit Shape Biascited by 118
- 2024MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenizationcited by 104
- 20243DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusioncited by 101
- 2024Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scalecited by 89
9 more
- 2024EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generationcited by 87
- 2025SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modelingcited by 79
- 2024Scaling Mesh Generation via Compressive Tokenizationcited by 73
- 2025DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement Learningcited by 65
- 2025TexVerse: A Universe of 3D Objects with High-Resolution Texturescited by 45
- 2025QuadGPT: Native Quadrilateral Mesh Generation with Autoregressive Modelscited by 12
- 2025MeshRipple: Structured Autoregressive Generation of Artist-Meshescited by 10
- 2025Topology-Preserved Auto-regressive Mesh Generation in the Manner of Weaving Silkcited by 7
- 2025Faithful Contouring: Near-Lossless 3D Voxel Representation Free from Iso-surfacecited by 4
Built on by
Citing papers per year: 2026: 1.
1 paper.
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- 2023Single Mesh Diffusion Models with Field Latents for Texture Generation
- 2026Nexus: Native Mesh Generation with Diffusion
- 2024CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner
- 20233DGen: Triplane Latent Diffusion for Textured Mesh Generation
- 2025Topology Sculptor, Shape Refiner: Discrete Diffusion Model for High-Fidelity 3D Meshes Generation
- 2024Topology-Aware Latent Diffusion for 3D Shape Generation
- 2023Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Models
- 2026FACE: A Face-based Autoregressive Representation for High-Fidelity and Efficient Mesh Generation