UniRig - AI Vision Models Tool

Overview

UniRig is an AI-based unified framework for automatic 3D model rigging. It leverages a GPT-like transformer to predict skeleton hierarchies and per-vertex skinning weights. The project automates the traditionally time-consuming rigging process for diverse 3D assets, including humans, animals, and objects.

Key Features

• Predicts skeleton hierarchies using a GPT-like transformer
• Estimates per-vertex skinning weights for mesh deformation
• Unified framework for automatic 3D model rigging
• Supports diverse asset types: humans, animals, and objects
• Reduces manual rigging steps by automating core tasks

Ideal Use Cases

• Automate rigging for human character models
• Generate rigs for animal models
• Rig object and prop meshes for animation
• Accelerate rigging in animation and game pipelines
• Batch-process large asset libraries for production

Getting Started

• Open the GitHub repository at https://github.com/VAST-AI-Research/UniRig
• Clone the repository to your local machine
• Install dependencies and environment as documented in the README
• Prepare and supply your 3D model files to the workflow
• Run the provided rigging scripts or model inference
• Validate and adjust predicted skeletons and skin weights
• Refer to repository examples and issues for troubleshooting

Pricing

Not disclosed; the repository does not specify pricing or commercial terms.

Key Information

• Category: Vision Models
• Type: AI Vision Models Tool