用3D高斯与发丝结合重建真实头发，支持直接编辑渲染。
Human Hair Reconstruction with Strand-Aligned 3D Gaussians
- 采用发丝与3D高斯双表示，实现精准头发建模。
- 在合成与真实场景中均达当前最佳效果，重建精度高。
- 结果可直接用于图形引擎，适合影视动画制作使用。
我们提出一种新型头发建模方法，结合传统发丝与3D高斯表示，从多视角数据中重建精确且逼真的发丝级发型。不同于近期使用无结构3D高斯建模人物的方法，本方法以3D折线（即发丝）形式重建头发。这一根本差异使生成的发型可直接用于现代计算机图形引擎进行编辑、渲染和模拟。我们的3D提升方法利用无结构高斯生成多视角真值数据，监督发丝拟合过程。发型本身采用所谓的“发丝对齐3D高斯”表示，融合发丝级先验与3D高斯泼溅的可微渲染能力。该方法命名为Gaussian Haircut，在合成与真实场景上评估，展现了发丝级头发重建任务的最先进性能。
原文摘要 · Abstract (English)
We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions from multi-view data. In contrast to recent approaches that leverage unstructured Gaussians to model human avatars, our method reconstructs the hair using 3D polylines, or strands. This fundamental difference allows the use of the resulting hairstyles out-of-the-box in modern computer graphics engines for editing, rendering, and simulation. Our 3D lifting method relies on unstructured Gaussians to generate multi-view ground truth data to supervise the fitting of hair strands. The hairstyle itself is represented in the form of the so-called strand-aligned 3D Gaussians. This representation allows us to combine strand-based hair priors, which are essential for realistic modeling of the inner structure of hairstyles, with the differentiable rendering capabilities of 3D Gaussian Splatting. Our method, named Gaussian Haircut, is evaluated on synthetic and real scenes and demonstrates state-of-the-art performance in the task of strand-based hair reconstruction.
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