研究人员开发了“Stitched Embeddings”，一个新颖的框架，在一个双向潜在空间中统一了3D服装模型及其对应的2D缝纫版型。这种方法消除了对物理模拟的需求，是传统方法的一项重大进步。通过利用预训练的3D基础模型的几何先验知识并采用BoxMesh中间表示，该系统可以有效地从3D网格重建版型，并支持从2D版型进行3D编辑，从而将神经3D视觉与服装制造联系起来。 AI
影响 该框架通过支持从2D版型直接进行3D编辑和提高服装重建效率，有可能简化数字时尚设计和制造。
排序理由 该集群包含一篇详细介绍3D服装建模和2D版型生成新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2607.00829v1 Announce Type: new Abstract: While garments are essential for realistic digital humans, their topological variety makes them much harder to model than parametric bodies. Traditional tailoring relies on 2D sewing patterns, yet bridging these patterns to 3D geome…
While garments are essential for realistic digital humans, their topological variety makes them much harder to model than parametric bodies. Traditional tailoring relies on 2D sewing patterns, yet bridging these patterns to 3D geometry currently requires physical simulations. We …