MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing
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Abstract (arXiv)
We introduce MeshPad, a generative approach that creates 3D meshes from sketch inputs. Building on recent advances in artist-reminiscent triangle mesh generation, our approach addresses the need for interactive mesh creation. To this end, we focus on enabling consistent edits by decomposing editing into 'deletion' of regions of a mesh, followed by 'addition' of new mesh geometry. Both operations are invoked by simple user edits of a sketch image, facilitating an iterative content creation process and enabling the construction of complex 3D meshes. Our approach is based on a triangle sequence-based mesh representation, exploiting a large Transformer model for mesh triangle addition and deletion. In order to perform edits interactively, we introduce a vertex-aligned speculative prediction strategy on top of our additive mesh generator. This speculator predicts multiple output tokens corresponding to a vertex, thus significantly reducing the computational cost of inference and accelerating the editing process, making it possible to execute each editing step in only a few seconds. Comprehensive experiments demonstrate that MeshPad outperforms state-of-the-art sketch-conditioned mesh generation methods, achieving more than 22% mesh quality improvement in Chamfer distance, and being preferred by 90% of participants in perceptual evaluations.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 52 of its 66 references that are in the map. First posted on arXiv 3 Mar 2025.
Builds on
52 of 66 references.
References · 52
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
- 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
- 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,512
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
- 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
- 2022Fast Inference from Transformers via Speculative Decodingcited by 1,653
- 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
- 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,290
- 2023Accelerating Large Language Model Decoding with Speculative Samplingcited by 1,006
- 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 687
- 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 553
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- 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
- 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
- 2019PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flowscited by 488
- 2023GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splattingcited by 335
- 2023LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Modelscited by 287
- 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 269
- 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 259
- 2016Shape Completion using 3D-Encoder-Predictor CNNs and Shape Synthesiscited by 219
- 2018Pix3D: Dataset and Methods for Single-Image 3D Shape Modelingcited by 218
- 2023XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchiescited by 189
- 2019Gradio: Hassle-Free Sharing and Testing of ML Models in the Wildcited by 178
- 2023AM-RADIO: Agglomerative Vision Foundation Model -- Reduce All Domains Into Onecited by 169
- 2023Locally Attentional SDF Diffusion for Controllable 3D Shape Generationcited by 130
- 20214DComplete: Non-Rigid Motion Estimation Beyond the Observable Surfacecited by 124
- 2024MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenizationcited by 104
- 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Modelscited by 103
- 2023TextDeformer: Geometry Manipulation using Text Guidancecited by 94
- 2024Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scalecited by 89
- 2024EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generationcited by 87
- 2019SG-NN: Sparse Generative Neural Networks for Self-Supervised Scene Completion of RGB-D Scanscited by 77
- 2023SKED: Sketch-guided Text-based 3D Editingcited by 73
- 2023SALAD: Part-Level Latent Diffusion for 3D Shape Generation and Manipulationcited by 66
- 2023PolyDiff: Generating 3D Polygonal Meshes with Diffusion Modelscited by 66
- 2024Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materialscited by 66
- 2024PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Modelscited by 62
- 2018Scan2Mesh: From Unstructured Range Scans to 3D Meshescited by 51
- 2024Generic 3D Diffusion Adapter Using Controlled Multi-View Editingcited by 47
- 2024Instant3dit: Multiview Inpainting for Fast Editing of 3D Objectscited by 44
- 2024DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Predictioncited by 33
- 2022Neural Shape Deformation Priorscited by 27
- 2024SketchDream: Sketch-based Text-to-3D Generation and Editingcited by 25
- 20243D Mesh Editing using Masked LRMscited by 18
- 2023LatentEditor: Text Driven Local Editing of 3D Scenescited by 17
- 2023InstructP2P: Learning to Edit 3D Point Clouds with Text Instructionscited by 14
- 2023Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapescited by 14
- 2024Edify 3D: Scalable High-Quality 3D Asset Generationcited by 10
- 2023SENS: Part-Aware Sketch-based Implicit Neural Shape Modelingcited by 8
- 2024Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalabilitycited by 8
50 most cited of 52 All 52 (JSON)
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Citing papers per year: 2026: 7.
7 papers.
- 2026neuralCAD-Edit: An Expert Benchmark for Multimodal-Instructed 3D CAD Model Editingcited by 3
- 2026DressWild: Feed-Forward Pose-Agnostic Garment Sewing Pattern Generation from In-the-Wild Imagescited by 2
- 2026TriFlow: Generating Artist-Like 3D Mesh Topology via Nearest-Vertex Vector Fieldscited by 2
- 2026EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learningcited by 1
- 2026RADmesh: Remesh-Aware Mesh Deformationcited by 0
- 2026AgenticCADedit: A Stateful, Tool-Mediated Agentic Approach to Multimodal 3D CAD Editingcited by 0
- 2026AnchorGen: Anchored Optimization for Customizable Generative 3D Designcited by 0
- 2026AnchorGen: Anchored Optimization for Customizable Generative 3D Design5 Oct 2026
- 2026AgenticCADedit: A Stateful, Tool-Mediated Agentic Approach to Multimodal 3D CAD Editing28 Aug 2026
- 2026RADmesh: Remesh-Aware Mesh Deformation17 Aug 2026
- 2026EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learning8 Jul 2026
- 2026TriFlow: Generating Artist-Like 3D Mesh Topology via Nearest-Vertex Vector Fields18 Jun 2026
- 2026neuralCAD-Edit: An Expert Benchmark for Multimodal-Instructed 3D CAD Model Editing17 Apr 2026
- 2026DressWild: Feed-Forward Pose-Agnostic Garment Sewing Pattern Generation from In-the-Wild Images18 Feb 2026