MeshQuery: Agentic Seam Planning for UV Parametrization

2026-10-01

AI Summary

This study addresses the reliance on manual intervention for seam planning in production-level automatic UV unwrapping of quadrilateral meshes. We propose a training-free agent-based method that leverages vision-language models (VLMs) integrated with domain knowledge. By employing query-based mesh representations and a domain-specific language (DSL), our approach decouples high-level intent planning from low-level edge selection, while introducing a feedback loop mechanism to iteratively refine seams. This design ensures compatibility across backend VLMs and enables scalability to extremely large meshes. Experimental results demonstrate that the proposed method reduces the number of charts by 2.9× and shortens seam length by 1.63×, achieving an 80.9% preference rate among professional artists.

Abstract

We present MeshQuery, a training-free agentic approach to automatic UV unwrapping of production-grade quad meshes. A Vision-Language Model (VLM) plans artist-aligned seams using a set of edge-selection tools, conditioned on domain-specific UV-unwrapping knowledge expressed in natural language and refined with a feedback loop. We design a queryable mesh representation together with a domain-specific language (DSL) that enables the agent to retrieve mesh information on demand, express a seam plan as a compact program of edge-selection operators over topological, geometric, and semantic mesh attributes, and iteratively refine it from UV quality feedback. On Adobe Substance 3D and Toys4K meshes, MeshQuery produces 2.9x/4.29x fewer charts and 1.63x/1.7x shorter seams than the strongest baseline, and professional artists prefer its results in 80.9% of comparisons. Ultimately, decoupling high-level intent planning from low-level edge selection and compact mesh representation lets MeshQuery run on different backend VLMs and scale to meshes an order of magnitude larger than autoregressive seam prediction

Problem

• UV unwrapping
• seam planning
• quad meshes
• mesh parametrization

Innovation

• Vision-Language Model
• UV Parametrization
• Domain-Specific Language
• Agentic Approach
• Seam Planning