OmniFaceRig: 跨多种3D角色拓扑的全自动内口感知面部绑定
OmniFaceRig: Fully Automatic Inner-Mouth-Aware Face Rigging Across Diverse 3D Character Topologies
AI总结：
提出全自动端到端管道OmniFaceRig，将静态表面网格转换为含内口几何的FACS绑定，支持人类、人形及多种动物拓扑，无需手动标注或模板。
摘要：
面部绑定——创建基于FACS的混合形状以及内口几何（牙齿、牙龈和舌头）——仍然是3D角色制作中的主要瓶颈。现有流程仍需要大量设计工作，特别是手动地标标注、每个角色的模板调整和内口放置。我们提出OmniFaceRig，一个全自动端到端管道，将静态表面仅3D角色网格（无预建模口腔）转换为内口感知的FACS绑定，包含多达155个混合形状、程序化拟合的牙齿、牙龈和舌头，以及重新打包的UV/纹理。OmniFaceRig支持多种拓扑——人类、人形、长吻动物（如狗、狼、狐狸）和短吻动物（如猫、熊、兔子、老虎）——无需手动地标、无需用户提供模板、无需每个资产的设置。该管道结合了混合VLM+CV可绑定性检查、多模型面部解析、密集关键点驱动的模板配准、程序化内口构建以及碰撞感知的混合形状迁移。对于非人类角色，OmniFaceRig选择拓扑特定的面部和内口模板，并使用碰撞感知的内口拟合来减少牙齿-面部交叉，而无需用户暴露于类别特定的调整。我们还公开发布了Omni-Bench，一个包含1000个双足3D角色的免费基准数据集，带有FACS面部混合形状和内口几何，涵盖人类、人形、猫、狗和其他动物。实验表明，在筛选后的Omni-Bench输入上，最终绑定成功率很高，分割集成几乎实现了完全的面部检测召回，以及可靠的内口放置和低穿透率。总之，OmniFaceRig为从静态生成的角色到动画就绪的面部绑定提供了一条自动化路径，适用于人类和非人类拓扑。
英文摘要：
Facial rigging - creating FACS-based blendshapes together with inner-mouth geometry (teeth, gums, and tongue) - remains a major bottleneck in 3D character production. Existing pipelines still require substantial designer effort, especially for manual landmark annotation, per-character template adjustment, and inner-mouth placement. We present OmniFaceRig, a fully automatic end-to-end pipeline that converts a static surface-only 3D character mesh, with no pre-modeled oral cavity, into an inner-mouth-aware FACS rig with up to 155 blendshapes, procedurally fitted teeth, gums, and tongue, and re-packed UV/texture. OmniFaceRig supports diverse topologies - humans, humanoids, long-muzzled animals (e.g., dogs, wolves, foxes), and short-muzzled animals (e.g., cats, bears, rabbits, tigers) - with no manual landmarks, no user-provided templates, and no per-asset setup. The pipeline combines hybrid VLM+CV riggability checking, multi-model face parsing, dense keypoint-driven template registration, procedural inner-mouth construction, and collision-aware blendshape transfer. For non-human characters, OmniFaceRig selects topology-specific face and inner-mouth templates and uses collision-aware inner-mouth fitting to reduce teeth-face intersections without exposing users to category-specific tuning. We also publicly release Omni-Bench, a freely available benchmark dataset of 1,000 biped 3D characters with FACS facial blendshapes and inner-mouth geometry, spanning humans, humanoids, cats, dogs, and other animals. Experiments show high final rigging success on screened Omni-Bench inputs, nearly complete face detection recall from the segmentation ensemble and reliable inner-mouth placement with low penetration. Together, OmniFaceRig provides an automatic path from static generated characters to animation-ready facial rigs across both human and non-human topologies.
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。
