In-editor, pure-C# deep-learning auto-rigger for s&box: 7 neural models turn any mesh into a skinned FBX + VMDL, with a live joint-editing preview and optional vast.ai cloud rigging.
C#
2
225 commits
updated Jul 5, 2026
README
Auto Rigger (DL)
Automatically rig 3D models into animation-ready s&box .vmdl files using
deep learning, entirely inside the editor and entirely in pure C#: no Blender,
no Python, no native DLLs. Skeletons are predicted by real neural networks
(full C# ports of the released research models, validated numerically against
PyTorch on the official weights).
Using it
- Install the library into your project and open View -> Auto Rigger (DL).
- Enable at least one model via Manage Models... (one-time setup; see below).
- Add Model: drop in
.fbx/.glb/.gltf/.objfiles. Each file is analyzed and rigged automatically with the best enabled model, or pick a specific model from the dropdown ("Auto" selects for you per mesh). - Preview: once a row finishes rigging, its eye button opens a preview - the textured model rendered see-through with the skeleton visible inside it (red joints, blue bones, the traditional convention). Scroll to zoom.
- Export: writes the skinned
.fbx(import it in Blender if you like) plus the generated.vmdl, compiled in place with its textures. Compiler errors (if any) surface on the row.
Models
| Model | What it is | Status |
|---|---|---|
| RigNet (SIGGRAPH 2020) | Graph networks predicting joints, hierarchy, and skin weights. | Available |
| UniRig (VAST-AI 2025) | 350M-parameter autoregressive skeleton transformer conditioned on a point-cloud shape encoder. | Available |
| SkinTokens / TokenRig (VAST-AI 2026) | UniRig's successor: skeleton and skin tokens generated as one sequence on a Qwen3 backbone, with native FSQ skin-VAE weights. | Available |
| MagicArticulate (ByteDance Seed3D 2025) | Autoregressive bone-pair transformer trained on Articulation-XL. | Available |
| Puppeteer (ByteDance Seed3D 2025) | Skeleton transformer with parent indices carried in the token sequence, plus a native skinning transformer (PartField features) for neural skin weights. | Available |
| RigAnything (Adobe 2025) | Autoregressive diffusion skeleton generation with neural skin weights. Noncommercial research license. | Available |
| Anymate (2025) | Three-stage neural rigging: joint prediction, connectivity, and neural skin weights (Apache-2.0). | Available |
Transformer models run deterministically (greedy decode) on CPU; expect one to several minutes per mesh depending on the model. SkinTokens, Puppeteer (with its skinning checkpoint installed) and RigAnything predict their own NEURAL skin weights; the other models use the library's geodesic voxel skinner.
Managing models
Manage Models... shows every supported model with its license, download
size, and a hardware verdict for your machine. Models your machine cannot run
are disabled automatically. Download fetches weights directly from the
authors' official distribution with progress and resume; nothing is
redistributed by this library, and an ATTRIBUTION.md is written next to the
weights. You can also load your own RigNet-format checkpoint zip.
Notes
- Engine-agnostic core in
Code/(whitelist-safe), editor UI inEditor/. - Development harness, PyTorch golden tests, and gate scripts live in
dev/(not part of the shipped library). - Attribution:
- RigNet: Xu, Zhou, Kalogerakis, Landreth, Singh, SIGGRAPH 2020 (GPL-3.0 or commercial license from UMass).
- UniRig: VAST-AI Research, One Model to Rig Them All (2025).
- SkinTokens: VAST-AI Research (2026).
- MagicArticulate: ByteDance Seed3D (2025), code Apache-2.0.
- Puppeteer: ByteDance Seed3D (2025).
- RigAnything: Liu et al., Adobe (SIGGRAPH TOG 2025). Adobe Research License: noncommercial research use only.
- Anymate: Deng et al. (2025), Apache-2.0.
- All model weights are downloaded by the user from the authors' official sources; this library ships no weights.
Cloud rigging (vast.ai)
For machines that cannot run a model locally, Cloud... rents a GPU on vast.ai for a single rig. Renting is never automatic: the picker lists offers with hourly rates and a worst-case cost, and nothing is charged until you click rent. The instance created for the job is recorded in a local ledger and destroyed with verification the moment results are back. Only that one instance is ever touched; pre-existing instances on your account are never enumerated or cancelled.
Roadmap
- Broader corpus validation and per-model quality presets.
Similar repos
In-editor, pure-C# deep-learning auto-rigger for s&box: 7 neural models turn any mesh into a skinned FBX + VMDL, with a live joint-editing preview and optional vast.ai cloud rigging.
C#
2
225 commits
updated Jul 5, 2026
README
Auto Rigger (DL)
Automatically rig 3D models into animation-ready s&box .vmdl files using
deep learning, entirely inside the editor and entirely in pure C#: no Blender,
no Python, no native DLLs. Skeletons are predicted by real neural networks
(full C# ports of the released research models, validated numerically against
PyTorch on the official weights).
Using it
- Install the library into your project and open View -> Auto Rigger (DL).
- Enable at least one model via Manage Models... (one-time setup; see below).
- Add Model: drop in
.fbx/.glb/.gltf/.objfiles. Each file is analyzed and rigged automatically with the best enabled model, or pick a specific model from the dropdown ("Auto" selects for you per mesh). - Preview: once a row finishes rigging, its eye button opens a preview - the textured model rendered see-through with the skeleton visible inside it (red joints, blue bones, the traditional convention). Scroll to zoom.
- Export: writes the skinned
.fbx(import it in Blender if you like) plus the generated.vmdl, compiled in place with its textures. Compiler errors (if any) surface on the row.
Models
| Model | What it is | Status |
|---|---|---|
| RigNet (SIGGRAPH 2020) | Graph networks predicting joints, hierarchy, and skin weights. | Available |
| UniRig (VAST-AI 2025) | 350M-parameter autoregressive skeleton transformer conditioned on a point-cloud shape encoder. | Available |
| SkinTokens / TokenRig (VAST-AI 2026) | UniRig's successor: skeleton and skin tokens generated as one sequence on a Qwen3 backbone, with native FSQ skin-VAE weights. | Available |
| MagicArticulate (ByteDance Seed3D 2025) | Autoregressive bone-pair transformer trained on Articulation-XL. | Available |
| Puppeteer (ByteDance Seed3D 2025) | Skeleton transformer with parent indices carried in the token sequence, plus a native skinning transformer (PartField features) for neural skin weights. | Available |
| RigAnything (Adobe 2025) | Autoregressive diffusion skeleton generation with neural skin weights. Noncommercial research license. | Available |
| Anymate (2025) | Three-stage neural rigging: joint prediction, connectivity, and neural skin weights (Apache-2.0). | Available |
Transformer models run deterministically (greedy decode) on CPU; expect one to several minutes per mesh depending on the model. SkinTokens, Puppeteer (with its skinning checkpoint installed) and RigAnything predict their own NEURAL skin weights; the other models use the library's geodesic voxel skinner.
Managing models
Manage Models... shows every supported model with its license, download
size, and a hardware verdict for your machine. Models your machine cannot run
are disabled automatically. Download fetches weights directly from the
authors' official distribution with progress and resume; nothing is
redistributed by this library, and an ATTRIBUTION.md is written next to the
weights. You can also load your own RigNet-format checkpoint zip.
Notes
- Engine-agnostic core in
Code/(whitelist-safe), editor UI inEditor/. - Development harness, PyTorch golden tests, and gate scripts live in
dev/(not part of the shipped library). - Attribution:
- RigNet: Xu, Zhou, Kalogerakis, Landreth, Singh, SIGGRAPH 2020 (GPL-3.0 or commercial license from UMass).
- UniRig: VAST-AI Research, One Model to Rig Them All (2025).
- SkinTokens: VAST-AI Research (2026).
- MagicArticulate: ByteDance Seed3D (2025), code Apache-2.0.
- Puppeteer: ByteDance Seed3D (2025).
- RigAnything: Liu et al., Adobe (SIGGRAPH TOG 2025). Adobe Research License: noncommercial research use only.
- Anymate: Deng et al. (2025), Apache-2.0.
- All model weights are downloaded by the user from the authors' official sources; this library ships no weights.
Cloud rigging (vast.ai)
For machines that cannot run a model locally, Cloud... rents a GPU on vast.ai for a single rig. Renting is never automatic: the picker lists offers with hourly rates and a worst-case cost, and nothing is charged until you click rent. The instance created for the job is recorded in a local ledger and destroyed with verification the moment results are back. Only that one instance is ever touched; pre-existing instances on your account are never enumerated or cancelled.
Roadmap
- Broader corpus validation and per-model quality presets.