mlsanityData to 14 Oct 2026

GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulation

arXiv 2403.11990 ↗First posted 18 Mar 2024cs.CVcited by 8

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Abstract (arXiv)

Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, mesh creation and manipulation is often time-consuming and labor-intensive. In this paper, we propose a highly controllable generative model, GetMesh, for mesh generation and manipulation across different categories. By taking a varying number of points as the latent representation, and re-organizing them as triplane representation, GetMesh generates meshes with rich and sharp details, outperforming both single-category and multi-category counterparts. Moreover, it also enables fine-grained control over the generation process that previous mesh generative models cannot achieve, where changing global/local mesh topologies, adding/removing mesh parts, and combining mesh parts across categories can be intuitively, efficiently, and robustly accomplished by adjusting the number, positions or features of latent points. Project page is https://getmesh.github.io.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 44 of its 49 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

44 of 49 references.

References · 44

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32 more
  1. 2020DiffWave: A Versatile Diffusion Model for Audio Synthesiscited by 1,354
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  18. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  19. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancementcited by 199
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  21. 20233DGen: Triplane Latent Diffusion for Textured Mesh Generationcited by 183
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 4; 2026: 1.

8 papers.

  1. 2024InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Modelscited by 433
  2. 2024Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformercited by 210
  3. 2024GaussianAnything: Interactive Point Cloud Flow Matching For 3D Object Generationcited by 12
  4. 2025LAMP: Data-Efficient Linear Affine Weight-Space Models for Parameter-Controlled 3D Shape Generation and Extrapolationcited by 4
  5. 2026OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generationcited by 2
  6. 2025MamTiff-CAD: Multi-Scale Latent Diffusion with Mamba+ for Complex Parametric Sequencecited by 1
  7. 2025QEMesh: Employing A Quadric Error Metrics-Based Representation for Mesh Generationcited by 0
  8. 2025ReconMOST: Multi-Layer Sea Temperature Reconstruction with Observations-Guided Diffusioncited by 0