Open surface components prevail in real industrial 3D content and support rendering, physical simulation and geometric editing. Garments serve as a typical open surface type, with numerous existing generation methods leveraging sewing patterns to generate 2D panels and stitch them into 3D shapes. Such domain-specific designs lack scalability and cannot generalize to shoes and accessories. Common field-based 3D generators prioritize watertight meshes and tend to create flawed double-layer structures on open surfaces. Though Trellis2 adopts field-free representation, its open surface results still contain normal and topology errors. We present AnySurf, a unified framework generating open, closed and hybrid 3D surfaces with accurate face orientation. Built on directed-edge enhanced Flexible Dual Grid (FDG-D), our representation retains normal direction information via oriented grid edges. We also propose ROS-FT post-training and a lightweight DE-Adapter with merely 1% extra parameters, facilitating directed edge learning while preserving original generation performance. We further construct Outfit3D dataset containing industrial garments and closed accessories. Our work transforms garment modeling into a universal 3D generation task. Experimental results demonstrate superior mesh quality and better practicality for downstream applications.

翻译：在真实工业3D内容中，开放曲面组件普遍存在，并支持渲染、物理仿真与几何编辑。服装作为典型的开放曲面类型，现有众多生成方法利用裁剪片生成二维裁片并缝合为三维形状。此类领域特定设计缺乏可扩展性，无法推广至鞋类与配饰。基于场的通用3D生成器优先处理水密网格，易在开放曲面上产生有缺陷的双层结构。尽管Trellis2采用无场表示，其开放曲面结果仍存在法向与拓扑误差。我们提出统一框架AnySurf，可生成具有准确面朝向的开放、封闭及混合3D曲面。基于定向边增强的灵活双网格（FDG-D）表示，该方法通过有向网格边保留法向方向信息。同时提出ROS-FT后训练与轻量级DE-Adapter，仅增加1%参数即可促进定向边学习并保持原始生成性能。进一步构建包含工业服装与封闭配件的Outfit3D数据集，将服装建模转化为通用3D生成任务。实验结果表明，该方法在下游应用中具有更优的网格质量与更好的实用性。