MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing

Abstract

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.

Cite

Text

Li et al. "MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing." International Conference on Computer Vision, 2025.

Markdown

[Li et al. "MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing." International Conference on Computer Vision, 2025.](https://mlanthology.org/iccv/2025/li2025iccv-meshpad/)

BibTeX

@inproceedings{li2025iccv-meshpad,
  title     = {{MeshPad: Interactive Sketch-Conditioned Artist-Reminiscent Mesh Generation and Editing}},
  author    = {Li, Haoxuan and Erkoç, Ziya and Li, Lei and Sirigatti, Daniele and Rosov, Vladislav and Dai, Angela and Nießner, Matthias},
  booktitle = {International Conference on Computer Vision},
  year      = {2025},
  pages     = {16227-16237},
  url       = {https://mlanthology.org/iccv/2025/li2025iccv-meshpad/}
}