mlsanityData to 7 Oct 2026

TetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes

arXiv 2405.20283 ↗First posted 30 May 2024cs.CV cs.GRcited by 20

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Abstract (arXiv)

We introduce TetSphere Splatting, a Lagrangian geometry representation designed for high-quality 3D shape modeling. TetSphere splatting leverages an underused yet powerful geometric primitive -- volumetric tetrahedral meshes. It represents 3D shapes by deforming a collection of tetrahedral spheres, with geometric regularizations and constraints that effectively resolve common mesh issues such as irregular triangles, non-manifoldness, and floating artifacts. Experimental results on multi-view and single-view reconstruction highlight TetSphere splatting's superior mesh quality while maintaining competitive reconstruction accuracy compared to state-of-the-art methods. Additionally, TetSphere splatting demonstrates versatility by seamlessly integrating into generative modeling tasks, such as image-to-3D and text-to-3D generation.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 90 of its 119 references that are in the map. First posted on arXiv 30 May 2024.

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90 of 119 references.

References · 90

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  4. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  5. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  6. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  7. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  8. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  9. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
  10. 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,574
  11. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  12. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
38 more
  1. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
  2. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
  3. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,204
  4. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
  5. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  6. 2016A Point Set Generation Network for 3D Object Reconstruction from a Single Imagecited by 972
  7. 2023MVDream: Multi-view Diffusion for 3D Generationcited by 928
  8. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 837
  9. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 834
  10. 2023Objaverse-XL: A Universe of 10M+ 3D Objectscited by 767
  11. 2024LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creationcited by 730
  12. 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
  13. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 684
  14. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 682
  15. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  16. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 638
  17. 2023SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Renderingcited by 611
  18. 2022Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemscited by 601
  19. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  20. 20163D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstructioncited by 587
  21. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
  22. 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
  23. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
  24. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
  25. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
  26. 2023Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priorscited by 395
  27. 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 379
  28. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  29. 2024GS-LRM: Large Reconstruction Model for 3D Gaussian Splattingcited by 344
  30. 2023Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Priorcited by 341
  31. 2019DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstructioncited by 332
  32. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
  33. 2023RealFusion: 360deg Reconstruction of Any Object from a Single Imagecited by 305
  34. 2024GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generationcited by 298
  35. 2022CLIP-Mesh: Generating textured meshes from text using pretrained image-text modelscited by 281
  36. 2023Generative Novel View Synthesis with 3D-Aware Diffusion Modelscited by 273
  37. 2024TripoSR: Fast 3D Object Reconstruction from a Single Imagecited by 227
  38. 2023DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Modelcited by 213

50 most cited of 90 All 90 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 12; 2026: 7.

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  1. 2024Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpaintingcited by 37
  2. 2025Dynamic Scene Reconstruction: Recent Advance in Real-time Rendering and Streamingcited by 8
  3. 2025Radiance Meshes for Volumetric Reconstructioncited by 6
  4. 20252D Triangle Splatting for Direct Differentiable Mesh Trainingcited by 5
  5. 2025Bezier Splatting for Fast and Differentiable Vector Graphics Renderingcited by 4
  6. 2025Neural Geometry Image-Based Representations with Optimal Transport (OT)cited by 2
  7. 2025Inverse Rendering for High-Genus Surface Meshes from Multi-View Imagescited by 2
  8. 2025Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compressioncited by 2
  9. 2026PAS3R: Pose-Adaptive Streaming 3D Reconstruction for Long Video Sequencescited by 2
  10. 2026Benchmarking PhD-Level Coding in 3D Geometric Computer Visioncited by 2
  11. 2025Shape from Semantics: 3D Shape Generation from Multi-View Semanticscited by 1
  12. 2025DensiCrafter: Physically-Constrained Generation and Fabrication of Self-Supporting Hollow Structurescited by 1
8 more
  1. 2025Med-PU: Point Cloud Upsampling for High-Fidelity 3D Medical Shape Reconstructioncited by 0
  2. 2025VoroLight: Learning Voronoi Surface Meshes via Sphere Intersectioncited by 0
  3. 2025PUFM++: Point Cloud Upsampling via Enhanced Flow Matchingcited by 0
  4. 2026Inverse Rendering for High-Genus 3D Surface Meshes from Multi-view Images with Persistent Homology Priorscited by 0
  5. 2026Vector Scaffolding: Inter-Scale Orchestration for Differentiable Image Vectorizationcited by 0
  6. 2026HoloTetSphere: Unified TetSphere Mesh Reconstruction for Physical Simulationscited by 0
  7. 2026CubicSplat: Differentiable Vector Graphics via Error-Bounded Forward Relaxationcited by 0
  8. 2026From Surfaces to Volumes: Registered Geometry for Protein Representation Learningcited by 0