---
license: apache-2.0
language:
- en
pretty_name: SceneRig Benchmark
size_categories:
- n<1K
tags:
- 3d
- robotics
- scene-reconstruction
- image-to-3d
configs:
- config_name: default
  data_files:
  - split: test
    path: data/test-*.parquet
---

# SceneRig Benchmark

**80 input images paired with SceneRig's settled Blender outputs and self-contained USDZ scenes**, reconstructed with **Claude Opus 5** (`claude-opus-5`).

The collection contains 44 simulator images, 18 real robot workspace images, and 18 smartphone, internet, or AI-generated images. These are reconstructed outputs, not ground-truth 3D annotations. All examples are in the `test` split.

[Project page](https://red-fairy.github.io/SceneRig/) · [Code](https://github.com/Red-Fairy/SceneRig)

## Files

```text
images/<scene_id>.png              Original benchmark input
scenes/<scene_id>/settled.blend    Saved final Blender output, with packed textures
scenes/<scene_id>/scene.usdz       USD scene with physics, geometry, textures, lights, and camera
manifest.jsonl                    Image-to-scene mapping, provenance, and checksums
release_metadata.json             Packaging and validation information
SHA256SUMS                        File checksums
data/test-00000-of-00001.parquet   Dataset table with embedded input images
```

Each of the 80 examples has exactly one input image, one Blender file, and one USDZ file. `image_path`, `settled_blend`, and `usdz` are paths relative to this repository. The table also records the scene ID, source family, image dimensions, base model, rigid-body count, saved verification statuses, and asset checksums.

| Source family | Images |
| --- | ---: |
| RoboDojo simulator | 24 |
| RoboLab simulator | 20 |
| Robot workspaces | 18 |
| Other images | 18 |
| **Total** | **80** |

## Download and use

```python
from datasets import load_dataset
from huggingface_hub import hf_hub_download

repo_id = "RedFairy/SceneRig-benchmark"
example = load_dataset(repo_id, split="test")[0]
image = example["image"]
blend_path = hf_hub_download(
    repo_id, example["settled_blend"], repo_type="dataset"
)
usdz_path = hf_hub_download(
    repo_id, example["usdz"], repo_type="dataset"
)
```

Download everything and verify its checksums:

```bash
hf download RedFairy/SceneRig-benchmark --repo-type dataset --local-dir SceneRig-benchmark
cd SceneRig-benchmark
sha256sum --check SHA256SUMS
```

Open `settled.blend` in Blender, or load `scene.usdz` in a USD-compatible application. Simulation requires a runtime that supports the authored USD Physics/PhysX schemas; a generic 3D viewer only displays the scene.

## Provenance and validation

- This release uses the original 80 runs in `static_scene_benchmark_final`. Each run records `claude-opus-5` as its model. Input image checksums match the preprocessing manifests.
- `settled.blend` is an unchanged copy of `scene/final/final.blend`, verified against the pipeline manifest. “Settled” refers to the pipeline's saved output after composition settling, not an additional simulation performed for this release. All 80 saved composition certifications report `passed`.
- USDZ files were generated from each run's saved `scene/isaac/scene.usd` using `UsdUtils.CreateNewUsdzPackage`, the packaging step documented in the project's Isaac export scripts. No reconstruction, simulation, or physics tuning was rerun.
- The 708 identity-mapped rigid-body transforms agree between the Blender and USD scenes within `1e-4` per matrix entry. USDZ packaging preserves those transforms exactly. Every package has resolved dependencies, uncompressed entries, and 64-byte file alignment.
- Blender files have packed textures and no linked-library dependencies; they were checked with Blender 4.5.13. Both native formats retain the saved Z-up scene convention. Materials and lighting may render differently between applications.
- The separate archived USD verifier reports `dynamic_verified` for 4 scenes and `unstable` for 76 under its recorded thresholds. These statuses are preserved in the table as `usd_simulation_status`; composition certification is a distinct check. This release does not claim that every scene passes that separate verifier.

The repository retains its Apache-2.0 license designation.