UniRig-AI Model Automates 3D Character Rigging Using SIGGRAPH'25 Research

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A new AI model called UniRig-AI, developed by Aaronjmars and based on research from Tsinghua University and Tripo published at SIGGRAPH 2025, automatically generates skeletal rigs and skinning weights for 3D models. The model supports a wide range of character types including humans, animals, and objects, and accepts common file formats such as .glb, .obj, .fbx, and .vrm. It uses a unified autoregressive framework combining skeleton tree tokenization with bone-point cross-attention to produce valid skeleton hierarchies and per-vertex skinning weights in a single pipeline. Compared to previous commercial and academic methods, UniRig-AI claims a 215% improvement in rigging accuracy and a 194% improvement in motion accuracy. The tool is designed to reduce manual rigging time for studios and developers working with large batches of 3D assets or algorithmic content pipelines.

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