mlsanityData to 14 Oct 2026

Dynamic Gaussians Mesh: Consistent Mesh Reconstruction from Dynamic Scenes

arXiv 2404.12379 ↗First posted 18 Apr 2024cs.CVcited by 22

Not on the map. Why?

Abstract (arXiv)

Modern 3D engines and graphics pipelines require mesh as a memory-efficient representation, which allows efficient rendering, geometry processing, texture editing, and many other downstream operations. However, it is still highly difficult to obtain high-quality mesh in terms of detailed structure and time consistency from dynamic observations. To this end, we introduce Dynamic Gaussians Mesh (DG-Mesh), a framework to reconstruct a high-fidelity and time-consistent mesh from dynamic input. Our work leverages the recent advancement in 3D Gaussian Splatting to construct the mesh sequence with temporal consistency from dynamic observations. Building on top of this representation, DG-Mesh recovers high-quality meshes from the Gaussian points and can track the mesh vertices over time, which enables applications such as texture editing on dynamic objects. We introduce the Gaussian-Mesh Anchoring, which encourages evenly distributed Gaussians, resulting better mesh reconstruction through mesh-guided densification and pruning on the deformed Gaussians. By applying cycle-consistent deformation between the canonical and the deformed space, we can project the anchored Gaussian back to the canonical space and optimize Gaussians across all time frames. During the evaluation on different datasets, DG-Mesh provides significantly better mesh reconstruction and rendering than baselines. Project page: https://www.liuisabella.com/DG-Mesh

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 44 of its 58 references that are in the map. First posted on arXiv 18 Apr 2024.

Builds on

44 of 58 references.

References · 44

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  2. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  3. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,465
  4. 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,198
  5. 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,157
  6. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
  7. 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 759
  8. 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 751
  9. 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
  10. 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 737
  11. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 651
  12. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
32 more
  1. 2023Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splattingcited by 476
  2. 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 471
  3. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 460
  4. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 441
  5. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
  6. 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
  7. 2023SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenescited by 347
  8. 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 346
  9. 2023Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesiscited by 344
  10. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
  11. 2020Neural Radiance Flow for 4D View Synthesis and Video Processingcited by 270
  12. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217
  13. 2023Gaussian-Flow: 4D Reconstruction with Dynamic 3D Gaussian Particlecited by 211
  14. 2022Monocular Dynamic View Synthesis: A Reality Checkcited by 200
  15. 2021BANMo: Building Animatable 3D Neural Models from Many Casual Videoscited by 197
  16. 2023Tracking Anything with Decoupled Video Segmentationcited by 197
  17. 2021Shape As Points: A Differentiable Poisson Solvercited by 187
  18. 2023Flexible Isosurface Extraction for Gradient-Based Mesh Optimizationcited by 139
  19. 2023Drivable 3D Gaussian Avatarscited by 120
  20. 2021LASR: Learning Articulated Shape Reconstruction from a Monocular Videocited by 116
  21. 2020MeshSDF: Differentiable Iso-Surface Extractioncited by 112
  22. 2019Deep Mesh Reconstruction from Single RGB Images via Topology Modification Networkscited by 106
  23. 20234K4D: Real-Time 4D View Synthesis at 4K Resolutioncited by 91
  24. 2022Neural Dual Contouringcited by 71
  25. 2021DOVE: Learning Deformable 3D Objects by Watching Videoscited by 61
  26. 2020Online Adaptation for Consistent Mesh Reconstruction in the Wildcited by 51
  27. 2020Implicit Mesh Reconstruction from Unannotated Image Collectionscited by 49
  28. 2023Deformable 3D Gaussian Splatting for Animatable Human Avatarscited by 44
  29. 2022Unbiased 4D: Monocular 4D Reconstruction with a Neural Deformation Modelcited by 25
  30. 2023NeuManifold: Neural Watertight Manifold Reconstruction with Efficient and High-Quality Rendering Supportcited by 25
  31. 2023NSF: Neural Surface Fields for Human Modeling from Monocular Depthcited by 21
  32. 2023MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Fieldcited by 12

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 6; 2026: 13.

22 papers.

Sort:

By area:

  1. 2024DynaSurfGS: Dynamic Surface Reconstruction with Planar-based Gaussian Splattingcited by 19
  2. 2026Motion 3-to-4: 3D Motion Reconstruction for 4D Synthesiscited by 15
  3. 2024Dynamic 2D Gaussians: Geometrically Accurate Radiance Fields for Dynamic Objectscited by 11
  4. 2024MaGS: Reconstructing and Simulating Dynamic 3D Objects with Mesh-adsorbed Gaussian Splattingcited by 9
  5. 2026Flow Equivariant World Models: Memory for Partially Observed Dynamic Environmentscited by 8
  6. 2025FastAvatar: Instant 3D Gaussian Splatting for Faces from Single Unconstrained Posescited by 7
  7. 2026One Video, One World: Turning Monocular Video into Physical 4D Scenescited by 6
  8. 2025Recovering Dynamic 3D Sketches from Videoscited by 2
  9. 2026Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fieldscited by 2
  10. 2025Advances in 4D Generation: A Surveycited by 1
  11. 2025TagSplat: Topology-Aware Gaussian Splatting for Dynamic Mesh Modeling and Trackingcited by 1
  12. 2025Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platformcited by 1
10 more
  1. 2026SV-GS: Sparse View 4D Reconstruction with Skeleton-Driven Gaussian Splattingcited by 1
  2. 2026SPRig: Self-Supervised Pose-Invariant Rigging from Mesh Sequencescited by 1
  3. 2025OMeGa: Joint Optimization of Explicit Meshes and Gaussian Splats for Robust Scene-Level Surface Reconstructioncited by 0
  4. 2026Gaussian Mesh Renderer for Lightweight Differentiable Renderingcited by 0
  5. 2026Detailed Geometry and Appearance from Opportunistic Motioncited by 0
  6. 20264D Vessel Reconstruction for Benchtop Thrombectomy Analysiscited by 0
  7. 2026D-Prism: Differentiable Primitives for Structured Dynamic Modelingcited by 0
  8. 2026GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesiscited by 0
  9. 2026Future Rendering neq Future Surface: A Benchmark and Dataset for Dynamic Surface Reconstruction Beyond the Observed Windowcited by 0
  10. 2026ToCo-Mesh: Topology-Consistent Dynamic Mesh Reconstruction via Adaptive Tessellation and Surface-Aligned 2DGScited by 0