mlsanityData to 14 Oct 2026

DMesh++: An Efficient Differentiable Mesh for Complex Shapes

arXiv 2412.16776 ↗First posted 21 Dec 2024cs.CV cs.GR cs.LGcited by 11

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Abstract (arXiv)

Recent probabilistic methods for 3D triangular meshes capture diverse shapes by differentiable mesh connectivity, but face high computational costs with increased shape details. We introduce a new differentiable mesh processing method that addresses this challenge and efficiently handles meshes with intricate structures. Our method reduces time complexity from O(N) to O(log N) and requires significantly less memory than previous approaches. Building on this innovation, we present a reconstruction algorithm capable of generating complex 2D and 3D shapes from point clouds or multi-view images. Visit our project page (https://sonsang.github.io/dmesh2-project) for source code and supplementary material.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 32 of its 58 references that are in the map. First posted on arXiv 21 Dec 2024.

Builds on

32 of 58 references.

References · 32

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  2. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  3. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,712
  4. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
  5. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,076
  6. 2021Volume Rendering of Neural Implicit Surfacescited by 996
  7. 2020Accelerating 3D Deep Learning with PyTorch3Dcited by 784
  8. 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 646
  9. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 460
  10. 2024CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assetscited by 455
  11. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 441
  12. 2019Soft Rasterizer: A Differentiable Renderer for Image-based 3D Reasoningcited by 420
20 more
  1. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 366
  2. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 314
  3. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 259
  4. 2019Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderercited by 221
  5. 2016Thingi10K: A Dataset of 10,000 3D-Printing Modelscited by 183
  6. 2024MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformerscited by 144
  7. 2023Flexible Isosurface Extraction for Gradient-Based Mesh Optimizationcited by 139
  8. 2024MeshLRM: Large Reconstruction Model for High-Quality Meshescited by 139
  9. 2024MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenizationcited by 104
  10. 2024Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scalecited by 89
  11. 2021MeshUDF: Fast and Differentiable Meshing of Unsigned Distance Field Networkscited by 76
  12. 2022Neural Dual Contouringcited by 71
  13. 2022NeuralUDF: Learning Unsigned Distance Fields for Multi-view Reconstruction of Surfaces with Arbitrary Topologiescited by 63
  14. 2020Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernelscited by 53
  15. 2022A Level Set Theory for Neural Implicit Evolution under Explicit Flowscited by 42
  16. 2023NeUDF: Leaning Neural Unsigned Distance Fields with Volume Renderingcited by 41
  17. 2023NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Supportcited by 25
  18. 2023Ghost on the Shell: An Expressive Representation of General 3D Shapescited by 24
  19. 2024SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshescited by 20
  20. 2024PoNQ: a Neural QEM-based Mesh Representationcited by 12

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 8.

11 papers.

  1. 2025SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modelingcited by 79
  2. 2026MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformercited by 7
  3. 2026LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flowcited by 6
  4. 2025Triangle Splatting+: Differentiable Rendering with Opaque Trianglescited by 5
  5. 2026From Blobs to Spokes: High-Fidelity Surface Reconstruction via Oriented Gaussianscited by 4
  6. 2026ExMesh: Explicit Mesh Reconstruction with Topology Adaptationcited by 2
  7. 2025Improving Multi-View Reconstruction via Texture-Guided Gaussian-Mesh Joint Optimizationcited by 0
  8. 2026Spinverse: Differentiable Physics for Permeability-Aware Microstructure Reconstruction from Diffusion MRIcited by 0
  9. 2026DiffGI: Differentiable Geometry Images for High-Fidelity Thin-Shell 3D Generationcited by 0
  10. 2026TopoSurfel: Closing the Loop between Gaussian Surfels and Meshes for Surface Reconstructioncited by 0
  11. 2026ExMesh++: From Multi-View Images to Relightable UV-PBR Mesh Assets via Topology-Adaptive Reconstruction and Decompositioncited by 0