Autoregressive (AR) models can generate high-quality low-poly meshes from point clouds, but they still operate in an all-or-nothing manner: when a local region is unsatisfactory, the entire mesh must be regenerated, wasting computation and destroying satisfactory mesh structure elsewhere. We introduce MeshFIM, a Fill-in-the-Middle (FIM) framework that regenerates a target region of a low-poly mesh conditioned on the surrounding context. MeshFIM addresses three mesh-specific challenges: enforcing exact attachment along the exposed boundary, preserving topological order in the context, and suppressing overflow beyond the intended region. It does so with five complementary design choices: boundary vertex markers, context positional embeddings, expanded context width, context augmentation, and a low-poly geometry encoder whose gated subtraction mechanism focuses generation on the missing region by leveraging the difference between the reference surface and the existing mesh. Detailed ablation studies are presented to show the effectiveness of every introduced component. Based on MeshFIM, we demonstrate two applications: interactive brush-based editing and automatic defect repair on low-poly mesh (see Figure 1). Last but not least, experiments show that MeshFIM outperforms a range of baselines in mesh refinement, mesh repair and whole mesh generation plus stitch-back scheme.

翻译：自回归（AR）模型能够从点云生成高质量的低多边形网格，但其运作方式仍为“全有或全无”：当局部区域不理想时，必须重新生成整个网格，这不仅浪费计算资源，还会破坏其他区域令人满意的网格结构。我们提出MeshFIM，一种基于填充式生成（Fill-in-the-Middle, FIM）的框架，可在给定周围上下文条件下重新生成低多边形网格的目标区域。MeshFIM解决了三个网格特有的挑战：沿暴露边界强制精确附着、保持上下文的拓扑顺序、以及抑制超出目标区域的溢出。为此，我们设计了五项互补策略：边界顶点标记、上下文位置嵌入、扩展上下文宽度、上下文增强，以及低多边形几何编码器——其门控减法机制通过利用参考曲面与现有网格之间的差异，将生成聚焦于缺失区域。通过详细消融实验验证了每个引入组件的有效性。基于MeshFIM，我们展示了两个应用：交互式笔刷编辑和低多边形网格的自动缺陷修复（见图1）。最后但同样重要的是，实验表明，在网格细化、网格修复以及整体网格生成加拼接方案中，MeshFIM均优于一系列基线方法。