从稀疏到浓密：无先验的多视角面部毛发级联重建
Wispy to Voluminous: Prior-free Multi-view Capture of Strand-level Facial Hair
AI总结：
提出从多视角图像自动重建面部毛发（胡须、眉毛等）的管线，将无结构3D高斯表示转换为显式曲线发丝，解决几何歧义，实现高保真发丝重建。
摘要：
面部毛发是个人身份的一个决定性特征，但仍然是数字头像的关键瓶颈。最近的体积方法实现了照片级真实感，但将毛发烘焙到面部几何中，阻碍了可编辑性，并且无法解析稀疏的、发丝状结构。同时，头皮毛发重建方法针对密集的毛发体积，无法适应面部毛发稀疏、空间变化的特性。我们提出了一种管线，从多视角图像自动重建面部毛发——胡须、髭须、睫毛和眉毛，将无结构的3D高斯表示转换为显式的基于曲线的发丝表示。我们分四个阶段解决几何歧义：（i）优化由跟踪头部几何约束的3D高斯，以强制早期光线终止并抑制次表面噪声；（ii）追踪连续发丝，对频繁交叉和极端曲率具有鲁棒性；（iii）将发丝接地到表面，并通过物理动机的先验解决根尖歧义；（iv）通过光度优化下的不透明度驱动密度控制来细化重建。据我们所知，这是第一个从3D高斯表示重建高保真面部毛发发丝的方法。恢复的发丝忠实地保留了面部毛发特征的朝向和稀疏模式，并生成可直接用于下游生产任务的资产，包括面部动画和物理模拟、几何梳理和转移、外观编辑以及基于物理的渲染。
英文摘要：
Facial hair is a defining trait of personal identity, yet remains a critical bottleneck for digital avatars. Recent volumetric methods achieve photorealism but bake hair into the underlying face geometry, preventing editability and failing to resolve sparse, strand-like structures. Meanwhile, scalp-hair reconstruction methods target dense hair volumes and do not transfer to the sparse, spatially-varying nature of facial hair. We present a pipeline that automatically reconstructs facial hair -- beard, mustache, lashes, and brows -- from multi-view images, converting an unstructured 3D Gaussian representation into an explicit curve-based strand representation. We resolve geometric ambiguities in four stages: (i) optimizing 3D Gaussians constrained by tracked head geometry to enforce early ray termination and suppress sub-surface noise; (ii) tracing continuous strands robust to frequent crossings and extreme curvature; (iii) grounding strands to the surface and resolving root-tip ambiguity via a physically-motivated prior; and (iv) refining the reconstruction through opacity-driven density control under photometric optimization. To our knowledge, this is the first method to reconstruct high-fidelity facial hair strands from a 3D Gaussian representation. The recovered strands faithfully preserve the orientation and sparsity patterns characteristic of facial hair, and yield assets immediately suitable for downstream production tasks, including facial animation and physical simulation, geometric grooming and transfer, appearance editing, and physics-based rendering.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
