MeshRipple: Structured Autoregressive Generation of Artist-Meshes
Not on the map. Why?
Abstract (arXiv)
Meshes serve as a primary representation for 3D assets. Autoregressive mesh generators serialize faces into sequences and train on truncated segments with sliding-window inference to cope with memory limits. However, this mismatch breaks long-range geometric dependencies, producing holes and fragmented components. To address this critical limitation, we introduce MeshRipple, which expands a mesh outward from an active generation frontier, akin to a ripple on a surface. MeshRipple rests on three key innovations: a frontier-aware BFS tokenization that aligns the generation order with surface topology; an expansive prediction strategy that maintains coherent, connected surface growth; and a sparse-attention global memory that provides an effectively unbounded receptive field to resolve long-range topological dependencies. This integrated design enables MeshRipple to generate meshes with high surface fidelity and topological completeness, outperforming strong recent baselines.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 80 of its 87 references that are in the map. First posted on arXiv 8 Dec 2025.
Builds on
80 of 87 references.
References · 80
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
- 2017Neural Discrete Representation Learningcited by 4,650
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
- 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
- 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
- 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
- 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,207
- 2023MVDream: Multi-view Diffusion for 3D Generationcited by 928
- 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 837
- 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 834
- 2023Objaverse-XL: A Universe of 10M+ 3D Objectscited by 767
- 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
38 more
- 2024LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creationcited by 730
- 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
- 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 684
- 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 682
- 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 638
- 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
- 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
- 2023Zero123++: a Single Image to Consistent Multi-view Diffusion Base Modelcited by 516
- 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 449
- 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
- 2024CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assetscited by 444
- 2025Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attentioncited by 391
- 2023Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Modelcited by 376
- 20203D-FRONT: 3D Furnished Rooms with layOuts and semaNTicscited by 375
- 2024SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusioncited by 364
- 2024GS-LRM: Large Reconstruction Model for 3D Gaussian Splattingcited by 344
- 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 342
- 20203D-FUTURE: 3D Furniture shape with TextUREcited by 306
- 2023Text-to-3D using Gaussian Splattingcited by 299
- 2024GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generationcited by 298
- 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 267
- 2023Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformerscited by 257
- 2023ImageDream: Image-Prompt Multi-view Diffusion for 3D Generationcited by 256
- 2023GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Modelscited by 255
- 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 254
- 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
- 2024CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Modelcited by 214
- 2023DMV3D: Denoising Multi-View Diffusion using 3D Large Reconstruction Modelcited by 213
- 2024Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformercited by 210
- 2025TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Modelscited by 204
- 2023MeshDiffusion: Score-based Generative 3D Mesh Modelingcited by 198
- 2023RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3Dcited by 168
- 2023PF-LRM: Pose-Free Large Reconstruction Model for Joint Pose and Shape Predictioncited by 165
- 2023DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Priorcited by 157
- 2024MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformerscited by 140
- 2023SweetDreamer: Aligning Geometric Priors in 2D Diffusion for Consistent Text-to-3Dcited by 134
- 2024Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Imagecited by 132
- 2024CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refinercited by 120
50 most cited of 80 All 80 (JSON)
Built on by
Citing papers per year: 2026: 8.
8 papers.
- 2026LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flowcited by 6
- 2026Strips as Tokens: Artist Mesh Generation with Native UV Segmentationcited by 2
- 2026SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivisioncited by 1
- 2026Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generationcited by 1
- 2026Block3D: Efficient Text-to-3D Generation via Block-Wise Diffusioncited by 1
- 2026SynVA: A Modular Toolkit for Vessel Generation and Aneurysm Editingcited by 0
- 2026MeshOctave: Vertex Split-and-Rewire Cascades for Native Mesh Generationcited by 0
- 2026OptimusMesh: Compact Autoregressive Mesh Generation from Point Clouds via Sparse Latent Pivotscited by 0
- 2026OptimusMesh: Compact Autoregressive Mesh Generation from Point Clouds via Sparse Latent Pivots1 Oct 2026
- 2026MeshOctave: Vertex Split-and-Rewire Cascades for Native Mesh Generation30 Sep 2026
- 2026Block3D: Efficient Text-to-3D Generation via Block-Wise Diffusion20 Aug 2026
- 2026LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flow12 Jul 2026
- 2026Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation30 Jun 2026
- 2026SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision25 Jun 2026
- 2026SynVA: A Modular Toolkit for Vessel Generation and Aneurysm Editing13 May 2026
- 2026Strips as Tokens: Artist Mesh Generation with Native UV Segmentation10 Apr 2026