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arXiv · 2602.04349

VecSet-Edit: Unleashing Pre-trained LRM for Mesh Editing from Single Image

Teng-Fang Hsiao·Bo-Kai Ruan·Yu-Lun Liu·Hong-Han Shuai
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Abstract

3D editing has emerged as a critical research area to provide users with flexible control over 3D assets. While current editing approaches predominantly focus on 3D Gaussian Splatting or multi-view images, the direct editing of 3D meshes remains underexplored. Prior attempts, such as VoxHammer, rely on voxel-based representations that suffer from limited resolution and necessitate labor-intensive 3D mask. To address these limitations, we propose \textbf{VecSet-Edit}, the first pipeline that leverages the high-fidelity VecSet Large Reconstruction Model (LRM) as a backbone for mesh editing. Our approach is grounded on a analysis of the spatial properties in VecSet tokens, revealing that token subsets govern distinct geometric regions. Based on this insight, we introduce Mask-guided Token Seeding and Attention-aligned Token Gating strategies to precisely localize target regions using only 2D image conditions. Also, considering the difference between VecSet diffusion process versus voxel we design a Drift-aware Token Pruning to reject geometric outliers during the denoising process. Finally, our Detail-preserving Texture Baking module ensures that we not only preserve the geometric details of original mesh but also the textural information. More details can be found in our project page: https://github.com/BlueDyee/VecSet-Edit/tree/main

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Teng-Fang Hsiao, Bo-Kai Ruan, Yu-Lun Liu, Hong-Han Shuai. 2026-06-25. VecSet-Edit: Unleashing Pre-trained LRM for Mesh Editing from Single Image. https://arxiv.org/abs/2602.04349

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