Rendering realistic cloth has always been a challenge due to its intricate structure. Cloth is made up of fibers, plies, and yarns, and previous curved-based models, while detailed, were computationally expensive and inflexible for large cloth. To address this, we propose a simplified approach. We introduce a geometric aggregation technique that reduces ray-tracing computation by using fewer curves, focusing only on yarn curves. Our model generates ply and fiber shapes implicitly, compensating for the lack of explicit geometry with a novel shadowing component. We also present a shading model that simplifies light interactions among fibers by categorizing them into four components, accurately capturing specular and scattered light in both forward and backward directions. To render large cloth efficiently, we propose a multi-scale solution based on pixel coverage. Our yarn shading model outperforms previous methods, achieving rendering speeds 3-5 times faster with less memory in near-field views. Additionally, our multi-scale solution offers a 20% speed boost for distant cloth observation.

翻译：由于织物结构的复杂性，渲染逼真的织物一直是一个挑战。织物由纤维、股线和纱线构成，以往基于曲线的模型尽管细节丰富，但在处理大尺寸织物时计算成本高昂且缺乏灵活性。为解决这一问题，我们提出了一种简化方法。我们引入了一种几何聚合技术，通过仅聚焦于纱线曲线，使用更少的曲线减少光线追踪计算量。我们的模型隐式生成股线和纤维形状，并通过一种新颖的阴影组件弥补显式几何结构的缺失。我们还提出了一种着色模型，通过将纤维间的光线交互分为四个分量来简化计算，能够精确捕捉前向和后向方向上的镜面反射光与散射光。为高效渲染大尺寸织物，我们提出了一种基于像素覆盖的多尺度解决方案。我们的纱线着色模型优于以往方法，在近场视角下可实现3-5倍的渲染速度提升且内存消耗更低。此外，我们的多尺度解决方案在远距离织物观测中额外实现了20%的速度提升。