PartUV: Part-Based UV Unwrapping of 3D Meshes
UV unwrapping flattens 3D surfaces to 2D with minimal distortion, often requiring the complex surface to be decomposed into multiple charts. Although extensively studied, existing UV unwrapping methods frequently struggle with AI-generated meshes, which are typically noisy, bumpy, and poorly conditioned. These methods often produce highly fragmented charts and suboptimal boundaries, introducing artifacts and hindering downstream tasks. We introduce PartUV, a part-based UV unwrapping pipeline that generates significantly fewer, part-aligned charts while maintaining low distortion. Built on top of a recent learning-based part decomposition method PartField, PartUV combines high-level semantic part decomposition with novel geometric heuristics in a top-down recursive framework. It ensures each chart's distortion remains below a user-specified threshold while minimizing the total number of charts. The pipeline integrates and extends parameterization and packing algorithms, incorporates dedicated handling of non-manifold and degenerate meshes, and is extensively parallelized for efficiency. Evaluated across four diverse datasets, including man-made, CAD, AI-generated, and Common Shapes, PartUV outperforms existing tools and recent neural methods in chart count and seam length, achieves comparable distortion, exhibits high success rates on challenging meshes, and enables new applications like part-specific multi-tiles packing. Our project page is at https://www.zhaoningwang.com/PartUV.
691fcf6ccce0eb9b6387af24
Zhaoning Wang
691fcf6ccce0eb9b6387af25
Xinyue Wei
admin_assigned
2025-11-21T10:46:11.563Z
646d6615da8e99940b7143cf
/avatars/e6e24e993fc4f3e9c7026b4c34bd1a25.svg
Xinyue Wei
sarahwei0210
user
sarahwei0210
691fcf6ccce0eb9b6387af26
Ruoxi Shi
691fcf6ccce0eb9b6387af27
Xiaoshuai Zhang
admin_assigned
2025-11-21T10:46:22.220Z
65f0bae3118cb0547bc2cf75
/avatars/3c13bf493298a2e052125328ec42c9ad.svg
Xiaoshuai Zhang
jetd
user
jetd
691fcf6ccce0eb9b6387af28
Hao Su
691fcf6ccce0eb9b6387af29
Minghua Liu
PartUV: Part-Based UV Unwrapping of 3D Meshes
UV unwrapping flattens 3D surfaces to 2D with minimal distortion, often requiring the complex surface to be decomposed into multiple charts. Although extensively studied, existing UV unwrapping methods frequently struggle with AI-generated meshes, which are typically noisy, bumpy, and poorly conditioned. These methods often produce highly fragmented charts and suboptimal boundaries, introducing artifacts and hindering downstream tasks. We introduce PartUV, a part-based UV unwrapping pipeline that generates significantly fewer, part-aligned charts while maintaining low distortion. Built on top of a recent learning-based part decomposition method PartField, PartUV combines high-level semantic part decomposition with novel geometric heuristics in a top-down recursive framework. It ensures each chart's distortion remains below a user-specified threshold while minimizing the total number of charts. The pipeline integrates and extends parameterization and packing algorithms, incorporates dedicated handling of non-manifold and degenerate meshes, and is extensively parallelized for efficiency. Evaluated across four diverse datasets, including man-made, CAD, AI-generated, and Common Shapes, PartUV outperforms existing tools and recent neural methods in chart count and seam length, achieves comparable distortion, exhibits high success rates on challenging meshes, and enables new applications like part-specific multi-tiles packing. Our project page is at https://www.zhaoningwang.com/PartUV.
PartUV, a part-based UV unwrapping pipeline, improves chart quality and reduces fragmentation for AI-generated meshes using part decomposition and geometric heuristics.
UV unwrapping part-based UV unwrapping PartUV PartField learning-based part decomposition geometric heuristics parameterization packing algorithms non-manifold degenerate meshes parallelization