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AniGen
AniGen generates rigged 3D assets from a single image for animation and simulation work.
The core image-generation example produces an asset you can drive with motion data. A separate reconstruction path fits a generated rig to recorded movement. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.
What it is
A single-image animatable 3D generator
The output combines a mesh for the visible shape, a skeleton for its joints, and skinning weights that connect the surface to those joints.
Why it stands out
Rigged output rather than static shape only
AniGen generates shape, skeleton, and skinning within one shared spatial representation. Its research tackles the mismatch that can arise when a static generated shape is passed to a separate rigging stage.
Availability
Public repo with models and demo path
Public research code and pretrained weights are available, with a command-line example and a Gradio demo for local use. The project also links to a hosted Hugging Face Space.
Why it matters
What makes it useful
A generated character needs more than its visible shape before you can pose it. AniGen supplies the rigging information along with the geometry, giving animation work a generated starting asset instead of leaving the entire rigging step separate.
What to know
Where it fits
Use it to explore image-to-asset workflows for animals, humanoids, or articulated objects. The generated rig can enter a 3D pipeline and be driven by motion data; motion selection and the rest of the animation workflow remain separate work.
Notable points
What stands out
The example saves mesh.glb for the rigged mesh, skeleton.glb for a skeleton visualization, and processed_image.png for the masked input. You can inspect the surface, the joint layout, and the image actually used as the condition separately. For finer skeleton detail, including fingers, the project recommends SS-Flow-Duet; for geometry generalization, it points to SS-Flow-Solo. That choice matters when the character needs finger joints rather than a less detailed skeleton.
Before using
What to review
Local setup is tested only on Linux and requires an NVIDIA GPU with at least 18GB of memory.
Download the required supporting weights as well as the AniGen checkpoints; the model instructions list them together.
For the controllable joint-density variant, the project warns that a density far from what suits the object can damage skinning weights.
The optional video-fitting path has separate dependencies and VGGT-Omega and LoMa checkouts. The separate video-editing application is described as a preview.
The CUBVH training extension is not needed for inference. Source code: MIT. See the repository and model pages for current component terms.
Check permission to use the source images or footage, including identifiable people, characters, and protected designs.
Reader fit
Who may find it relevant
Character and simulation builders exploring how an image can become a movable 3D asset.
Researchers who want the code, pretrained checkpoints, and separate mesh and skeleton outputs.
A different starting point if you already have a finished mesh and only need to add a rig: AniGen begins with an image.
Editorial note
Why LifeHubber lists it
We list AniGen because its optional reconstruction path connects a generated rig to movement observed in a video. It builds the asset from the first frame, then fits the rig across the recorded sequence. For researchers starting with footage of a moving subject, that offers a way to study how observed movement can guide a generated 3D asset, beyond creating its shape from one picture.
Source links
Source materials
Reader note
Before relying on this entry
LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.
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