Humanoid rigging gets better control and stable garment bones
TailorRig: Controllable and Structured Auxiliary Skeleton Generation for Garment-Aware Rigging
Computer Vision and Pattern Recognition
Summary
Making digital characters that wear complex clothes is hard because their skeletons need lots of extra bones for the clothes to move naturally. The authors created TailorRig, a system that lets artists design both the main body skeleton and these extra bones with clear labels and control. This helps avoid issues where moving one bone accidentally affects unrelated parts, making animations look weird. The system also uses a new way to assign how the skin moves with the bones, improving stability and accuracy. They tested TailorRig on many characters and a large dataset, showing it works better than existing methods.
What this means in practice
- •For character animators: Create complex garment skeletons with precise artist control to improve animation quality and stability on humanoid characters.
- •For game developers: Integrate dense, stable auxiliary skeletons in characters for better deformation and realistic cloth movement in games.
Authors
Yajing Chen, Xin Chen, Saidan Lu, Yeqi Yuan, Weikai Chen, Changyu Hu, Cheng Zeng, Xin Wang
Abstract
Humanoid rigging for modern characters with complex garments remains challenging due to the need for dense auxiliary skeletons and precise skinning control. Existing automatic methods primarily recover rigs from geometry, providing limited artist control over auxiliary articulation and often lacking explicit semantic or kinematic-chain structure for dense garment bones, leading to instability and weight bleeding. We present TailorRig, a framework that reformulates garment-aware humanoid rigging as a structured, controllable full-rig generation problem. This formulation shifts the goal from automatic rig recovery to artist-driven rig authoring, where both body-template compatibility and auxiliary articulation are explicit design choices. TailorRig exposes two explicit axes of artist control within a unified framework: a user-specified body skeleton template that preserves body-rig compatibility, and artist-provided semantic labels that drive an autoregressive generator to synthesize requested category-specific auxiliary bone chains. To robustly assign skinning weights under dense skeletal configurations, we further introduce a hierarchical chain-to-bone formulation: vertices are first associated to a kinematic chain, and bone weights are then refined within that chain, reducing weight bleeding between spatially adjacent but semantically unrelated structures. We evaluate TailorRig on a diverse set of characters and introduce Human-Mix, a large-scale dataset of over 38,000 humanoid models curated for garment-aware rigging. Experiments show that TailorRig improves skeleton accuracy, deformation stability, controllability, and practical usability over existing methods.