# One Model to Rig Them All: Diverse Skeleton Rigging with UniRig

arXiv: https://arxiv.org/abs/2504.12451 · HTML: https://mlsanity.com/paper/2504.12451/

## Key facts

- Cited by 45 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Apr 2025.

## Built on by (most cited first, 30 of 45)

- [Puppeteer: Rig and Animate Your 3D Models](https://mlsanity.com/paper/2508.10898/) (2025)
- [iTACO: Interactable Digital Twins of Articulated Objects from Casually Captured RGBD Videos](https://mlsanity.com/paper/2506.08334/) (2025)
- [Motion 3-to-4: 3D Motion Reconstruction for 4D Synthesis](https://mlsanity.com/paper/2601.14253/) (2026)
- [Hunyuan3D Studio: End-to-End AI Pipeline for Game-Ready 3D Asset Generation](https://mlsanity.com/paper/2509.12815/) (2025)
- [PhysRig: Differentiable Physics-Based Skinning and Rigging Framework for Realistic Articulated Object Modeling](https://mlsanity.com/paper/2506.20936/) (2025)
- [Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimization](https://mlsanity.com/paper/2506.11430/) (2025)
- [AnimaMimic: Imitating 3D Animation from Video Priors](https://mlsanity.com/paper/2512.14133/) (2025)
- [One Video, One World: Turning Monocular Video into Physical 4D Scenes](https://mlsanity.com/paper/2606.31388/) (2026)
- [Engine-Native Editable 3D World Reconstruction with Objects and Lighting](https://mlsanity.com/paper/2607.20889/) (2026)
- [Stable Part Diffusion 4D: Multi-View RGB and Kinematic Parts Video Generation](https://mlsanity.com/paper/2509.10687/) (2025)
- [Skin Tokens: A Learned Compact Representation for Unified Autoregressive Rigging](https://mlsanity.com/paper/2602.04805/) (2026)
- [FairyGen: Storied Cartoon Video from a Single Child-Drawn Character](https://mlsanity.com/paper/2506.21272/) (2025)
- [BiMotion: B-spline Motion for Text-guided Dynamic 3D Character Generation](https://mlsanity.com/paper/2602.18873/) (2026)
- [PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation](https://mlsanity.com/paper/2506.21076/) (2025)
- [AniGen: Unified S3 Fields for Animatable 3D Asset Generation](https://mlsanity.com/paper/2604.08746/) (2026)
- [RigAnyFace: Scaling Neural Facial Mesh Auto-Rigging with Unlabeled Data](https://mlsanity.com/paper/2511.18601/) (2025)
- [Topology-Agnostic Animal Motion Generation from Text Prompt](https://mlsanity.com/paper/2512.10352/) (2025)
- [Stroke3D: Lifting 2D strokes into rigged 3D model via latent diffusion models](https://mlsanity.com/paper/2602.09713/) (2026)
- [HEIR: Learning Graph-Based Motion Hierarchies](https://mlsanity.com/paper/2510.26786/) (2025)
- [MimiCAT: Mimic with Correspondence-Aware Cascade-Transformer for Category-Free 3D Pose Transfer](https://mlsanity.com/paper/2511.18370/) (2025)
- [MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos](https://mlsanity.com/paper/2601.02716/) (2026)
- [SPRig: Self-Supervised Pose-Invariant Rigging from Mesh Sequences](https://mlsanity.com/paper/2602.12740/) (2026)
- [SK-Adapter: Skeleton-Based Structural Control for Native 3D Generation](https://mlsanity.com/paper/2603.14152/) (2026)
- [Follow Your Track: Precise Skeleton Animation Controlled by 3D Trajectories](https://mlsanity.com/paper/2606.25344/) (2026)
- [ViP-Rig: Visual-Prompted Controllable Rigging](https://mlsanity.com/paper/2607.27982/) (2026)
- [UniMate: One Unified Model to Animate Diverse Skeletons](https://mlsanity.com/paper/2609.05415/) (2026)
- [Make-It-Poseable: Feed-forward Latent Posing Model for 3D Characters](https://mlsanity.com/paper/2512.16767/) (2025)
- [SkeletonGaussian: Editable 4D Generation through Gaussian Skeletonization](https://mlsanity.com/paper/2602.04271/) (2026)
- [PhysSkin: Real-Time and Generalizable Physics-Based Animation via Self-Supervised Neural Skinning](https://mlsanity.com/paper/2603.23194/) (2026)
- [UNICA: A Unified Neural Framework for Controllable 3D Avatars](https://mlsanity.com/paper/2604.02799/) (2026)

## Abstract (arXiv)

The rapid evolution of 3D content creation, encompassing both AI-powered methods and traditional workflows, is driving an unprecedented demand for automated rigging solutions that can keep pace with the increasing complexity and diversity of 3D models. We introduce UniRig, a novel, unified framework for automatic skeletal rigging that leverages the power of large autoregressive models and a bone-point cross-attention mechanism to generate both high-quality skeletons and skinning weights. Unlike previous methods that struggle with complex or non-standard topologies, UniRig accurately predicts topologically valid skeleton structures thanks to a new Skeleton Tree Tokenization method that efficiently encodes hierarchical relationships within the skeleton. To train and evaluate UniRig, we present Rig-XL, a new large-scale dataset of over 14,000 rigged 3D models spanning a wide range of categories. UniRig significantly outperforms state-of-the-art academic and commercial methods, achieving a 215% improvement in rigging accuracy and a 194% improvement in motion accuracy on challenging datasets. Our method works seamlessly across diverse object categories, from detailed anime characters to complex organic and inorganic structures, demonstrating its versatility and robustness. By automating the tedious and time-consuming rigging process, UniRig has the potential to speed up animation pipelines with unprecedented ease and efficiency. Project Page: https://zjp-shadow.github.io/works/UniRig/