一键生成含牙龈舌头的3D角色面部绑定,支持人与动物多种造型。
OmniFaceRig: Fully Automatic Inner-Mouth-Aware Face Rigging Across Diverse 3D Character Topologies
- 全自动流程:无须手动标注或模板调整,直接从静态网格生成带口腔结构的面部绑定。
- 可处理155个混合形状,对猫狗等动物也实现低穿透率的牙齿-面部精准适配。
- 适合游戏动画、影视建模师,尤其节省非人类角色的面部绑定工作量。
面部绑定——构建基于FACS的混合形状并包含牙齿、牙龈和舌头等内部口腔几何结构——仍是3D角色制作中的主要瓶颈。现有流程仍需大量设计者投入,尤其在人工地标标注、逐角色模板调整及内部口腔定位方面。本文提出OmniFaceRig,一个完全自动的端到端管道,将仅含表面的3D角色网格(无预建口腔腔体)转换为包含最多155个混合形状、程序化生成的牙齿、牙龈与舌头,并重新打包UV/纹理的内口感知型FACS绑定。该管道支持多样拓扑:人类、类人、长吻动物(如狗、狼、狐狸)、短吻动物(如猫、熊、兔子、老虎),且无需人工地标、无需用户提供的模板,也无需资产级设置。其结合了混合视觉语言模型+计算机视觉的可绑定性检测、多模型人脸解析、密集关键点驱动的模板注册、程序化内口构造以及碰撞感知的混合形状迁移。对于非人类角色,OmniFaceRig选择拓扑特异性的人脸与内口模板,并采用碰撞感知的内口拟合,有效减少牙齿与面部交叠,无需用户进行类别特定调优。同时,我们公开发布Omni-Bench,一个包含1000个双足3D角色的免费基准数据集,涵盖人类、类人、猫、狗及其他动物,均配有FACS面部混合形状与内口几何结构。实验表明,在筛选后的Omni-Bench输入上,最终绑定成功率高,分割集成实现近乎完整的面部检测召回率,并保证可靠的内口定位与低穿透率。
原文摘要 · Abstract (English)
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.
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