# zhan-xu/RigNet

Code for SIGGRAPH 2020 paper "RigNet: Neural Rigging for Articulated Characters"

Repository: https://github.com/zhan-xu/RigNet
Canonical: https://ross.abutalabs.com/products/rignet
Language: Python
License: GPL-3.0
License Family: copyleft
Last push: 2024-11-04T07:25:05+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2323, "days_push": 667, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1519, forks 205 (observed 2026-08-28T04:04:57.585041+00:00)

## What it is
RigNet is a PyTorch implementation of the SIGGRAPH 2020 paper on neural rigging for articulated 3D characters. It takes a character mesh as input and automatically predicts a skeleton and skinning weights, outputting rigs that can be converted to FBX for use in animation tools.

## Use cases
- automatically rig a 3d character mesh
- generate skeleton and skin weights from an obj file
- prepare articulated characters for animation
- convert static character models into rigged fbx files
- research on neural rigging and mesh analysis

## When to choose
- you need to automate rigging of humanoid or articulated character meshes
- you want a research baseline or to build on neural rigging methods
- you can run PyTorch with CUDA on Linux or Windows

## When to avoid
- you need a polished production tool with a GUI rather than research scripts
- your meshes cannot be simplified to 1K-5K vertices
- you need permissive licensing - the code is GPL-3.0

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, deep-learning, computer-vision, graphics, animation
- domain: computer-vision, graphics, machine-learning
- platform: windows, python
- tags: character-rigging, 3d-meshes, siggraph, pytorch, research-code, blender-addon, game-development, linux, gpu

## Member repositories
- zhan-xu/RigNet (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:57.585041+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:31:59.104056+00:00, confidence not recorded.
  - readme: https://github.com/zhan-xu/RigNet (fetched 2026-08-28T04:04:57.585041+00:00, sha 2a8c9f51ba2c)
- Data as of 2026-08-30T08:39:29.467469+00:00.