README.md

---
license: other
license_name: 3d-front-license-nc
license_link: https://3dfront.github.io/
library_name: worldflow3d
tags:
  - 3d-scene-generation
  - flow-matching
  - diffusers
  - indoor
  - front3d
  - non-commercial
---

# WorldFlow3D — Front3D (indoor) models

Layout-conditioned 3D indoor-scene generation (3D-FRONT), as a coarse → color
refinement flow-matching cascade. Use with the
[`worldflow3d`](https://github.com/princeton-computational-imaging/WorldFlow3D)
package (`pip install worldflow3d`).

> **License.** These models are trained on the **3D-FRONT** dataset and are
> released for **non-commercial / research use** under the 3D-FRONT dataset
> terms. The `worldflow3d` *code* is Apache-2.0, but that license does not grant
> rights to these 3D-FRONT-derived weights. See the 3D-FRONT dataset terms.

The **Waymo** (outdoor) models are trained on the Waymo Open Dataset and live in
a separate repo, [`pci-lab/worldflow3d-waymo`](https://huggingface.co/pci-lab/worldflow3d-waymo),
under the Waymo Dataset License (non-commercial).

## Cascade stages

| Subfolder | Role |
|-----------|------|
| `front3d-coarse` | coarse layout-conditioned generation (direct-diffusion) |
| `front3d-color` | source-flow + color refinement (UNet in=4, color mesh sidecar) |

## Usage

```python
from worldflow3d import WorldFlow3DPipeline

pipe = WorldFlow3DPipeline.from_hub(
    "pci-lab/worldflow3d", stage="front3d-coarse",
    refinement_stages=["front3d-color"], device="cuda",
)
```

See the [GitHub repo](https://github.com/princeton-computational-imaging/WorldFlow3D)
for full docs and the `generate_indoor` CLI.