mlsanityData to 14 Oct 2026

VertexRegen: Mesh Generation with Continuous Level of Detail

arXiv 2508.09062 ↗First posted 12 Aug 2025cs.GR cs.CV cs.LGcited by 16

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Abstract (arXiv)

We introduce VertexRegen, a novel mesh generation framework that enables generation at a continuous level of detail. Existing autoregressive methods generate meshes in a partial-to-complete manner and thus intermediate steps of generation represent incomplete structures. VertexRegen takes inspiration from progressive meshes and reformulates the process as the reversal of edge collapse, i.e. vertex split, learned through a generative model. Experimental results demonstrate that VertexRegen produces meshes of comparable quality to state-of-the-art methods while uniquely offering anytime generation with the flexibility to halt at any step to yield valid meshes with varying levels of detail.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 45 of its 60 references that are in the map. First posted on arXiv 12 Aug 2025.

Builds on

45 of 60 references.

References · 45

  1. 2023Visual Instruction Tuningcited by 7,869
  2. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,512
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  4. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,041
  5. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
  6. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
  7. 2023Objaverse-XL: A Universe of 10M+ 3D Objectscited by 774
  8. 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 699
  9. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 689
  10. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 651
  11. 2023SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Renderingcited by 616
  12. 2016Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modelingcited by 558
33 more
  1. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 553
  2. 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
  3. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  4. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 460
  5. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 458
  6. 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
  7. 2024InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Modelscited by 433
  8. 2021Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapescited by 426
  9. 2022SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generationcited by 288
  10. 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 269
  11. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 259
  12. 2023Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representationcited by 228
  13. 2019BSP-Net: Generating Compact Meshes via Binary Space Partitioningcited by 206
  14. 2024MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformerscited by 144
  15. 2024MeshLRM: Large Reconstruction Model for High-Quality Meshescited by 139
  16. 2022VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Gridscited by 133
  17. 2022Diffusion-SDF: Text-to-Shape via Voxelized Diffusioncited by 128
  18. 2024MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenizationcited by 104
  19. 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Modelscited by 103
  20. 2024Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scalecited by 89
  21. 2024EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generationcited by 87
  22. 2024Scaling Mesh Generation via Compressive Tokenizationcited by 73
  23. 2023PolyDiff: Generating 3D Polygonal Meshes with Diffusion Modelscited by 66
  24. 2024Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materialscited by 66
  25. 2024MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Modelcited by 55
  26. 2018Scan2Mesh: From Unstructured Range Scans to 3D Meshescited by 51
  27. 2024PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidancecited by 50
  28. 2020Deep Implicit Volume Compressioncited by 26
  29. 2023NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Supportcited by 25
  30. 2025DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusioncited by 23
  31. 2024Bayesian Diffusion Models for 3D Shape Reconstructioncited by 19
  32. 2023Neural Progressive Meshescited by 13
  33. 2024Neural Gaussian Scale-Space Fieldscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 12.

16 papers.

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