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---
license: cc-by-nc-4.0
task_categories:
- robotics
- image-to-3d
language: en
tags:
- 3d-gaussian-splatting
- vln
- embodied-navigation
- isaac-sim
- omniverse
- usdz
---

# SAGE-3D InteriorGS USDZ: USDZ-Format 3D Gaussian Scenes for Isaac Sim

[Paper](https://huggingface.co/papers/2510.21307) | [Project Page](https://sage-3d.github.io/) | [Code](https://github.com/Galery23/SAGE-3D_Official)

InteriorGS dataset converted to USDZ format for seamless integration with NVIDIA Omniverse and Isaac Sim platforms.

<div align="center">
  <img src="./src/SAGE-3D_InteriorGS_usdz.png" alt="SAGE-3D InteriorGS usdz">
  <p><em>USDZ format InteriorGS data captured on Issac Sim 5.0.</em></p>
</div>

---

## πŸ“’ News

- **2025-12-15**: Released SAGE-3D InteriorGS USDZ dataset with 1,000 converted scenes.

---

## πŸ“‹ Overview

While the original [InteriorGS dataset](https://huggingface.co/datasets/spatialverse/InteriorGS) provides high-quality 3D Gaussian Splatting scenes in compressed PLY format, these files are not directly compatible with modern simulation platforms like NVIDIA Isaac Sim and Omniverse. To bridge this gap, we present **SAGE-3D InteriorGS USDZ**, a format-converted version of the entire InteriorGS dataset.

This dataset provides:

- **1,000 indoor scenes** in USDZ format ready for Isaac Sim 5.0+
- **Photorealistic rendering quality** preserved from original 3DGS data
- **Direct compatibility** with NVIDIA Omniverse and Isaac Sim

### Conversion Pipeline

The conversion is performed using NVIDIA's [3DGRUT library](https://github.com/nv-tlabs/3dgrut):

```
InteriorGS compressed PLY β†’ Decompressed PLY β†’ USDZ (3DGRUT)
```

The USDZ format uses an extension of the `UsdVolVolume` Schema specifically designed for 3D Gaussian rendering in Isaac Sim, enabling:

**Real-time rendering** - Leverage Isaac Sim's optimized 3DGS renderer  
**Physics simulation** - Combine with [collision meshes](https://huggingface.co/datasets/spatialverse/InteriorGS) for embodied AI  
**Platform compatibility** - Work with Omniverse ecosystem tools

---

## πŸ—‚οΈ Dataset Structure

```
InteriorGS_usdz/
β”œβ”€β”€ 839873.usdz        # Scene in USDZ format
β”œβ”€β”€ 839874.usdz
β”œβ”€β”€ 839875.usdz
└── ...                # 1,000 scenes total
```

---

## ✨ Sample Usage

This section demonstrates how to use this USDZ dataset within the SAGE-3D framework, specifically how to build USDA scene files with integrated collision bodies for Isaac Sim.

**Prerequisites:**
1.  Install `splat-transform` and `3DGRUT` as described in the [project's GitHub repository](https://github.com/Galery23/SAGE-3D_Official#prerequisites).
2.  Download the original [InteriorGS dataset](https://huggingface.co/datasets/spatialverse/InteriorGS) (compressed PLY files) and the [SAGE-3D Collision Mesh Dataset](https://huggingface.co/datasets/spatialverse/SAGE-3D_Collision_Mesh).

**Step 1: Convert Compressed PLY to Original PLY (if starting from original InteriorGS)**

```bash
# Example: Convert a single scene
splat-transform /path/to/InteriorGS/0001_839920/3dgs_compressed.ply \
    /path/to/output/0001_839920.ply
```

**Step 2: Convert PLY to USDZ (if starting from original InteriorGS)**

```bash
# Example: Convert a single scene
python -m threedgrut.export.scripts.ply_to_usd \
    /path/to/ply/0001_839920.ply \
    --output_file /path/to/usdz/0001_839920.usdz
```
*Note: This dataset (`spatialverse/SAGE-3D_InteriorGS_usdz`) already provides the USDZ files, so you can directly use them instead of performing Steps 1 and 2.*

**Step 3: Build USDA Scene Files with Collision Meshes**

To use the USDZ scenes with physics simulation in Isaac Sim, they need to be combined with collision meshes and converted to USDA format.

```bash
python Code/benchmark/scene_data/sage3d_usda_builder.py \
    --usdz-dir /path/to/usdz_dataset \
    --out-dir /path/to/output/usda \
    --template Data/template.usda \
    --usdz-placeholder "@usdz_root[gauss.usda]@" \
    --collision-placeholder "@collision_root@" \
    --usdz-path-template "/path/to/usdz_dataset/{scene_id}.usdz[gauss.usda]" \
    --collision-path-template "/path/to/collision_mesh_dataset/{scene_id}/{scene_id}_collision.usd" \
    --overwrite
```
*Replace `/path/to/usdz_dataset` with the local path to this Hugging Face dataset, and `/path/to/collision_mesh_dataset` with the local path to `spatialverse/SAGE-3D_Collision_Mesh`.*

---

## πŸ”— Related Datasets

This dataset is part of the **SAGE-3D** project:

1.  **InteriorGS**: Original 3DGS scenes with semantic annotations  
    β†’ [spatialverse/InteriorGS](https://huggingface.co/datasets/spatialverse/InteriorGS)

2.  **SAGE-3D InteriorGS USDZ** (This dataset): USDZ format for Isaac Sim  
    β†’ [spatialverse/SAGE-3D_InteriorGS_usdz](https://huggingface.co/datasets/spatialverse/SAGE-3D_InteriorGS_usdz)

3.  **SAGE-3D Collision Mesh**: Physics-enabled collision bodies  
    β†’ [spatialverse/SAGE-3D_Collision_Mesh](https://huggingface.co/datasets/spatialverse/SAGE-3D_Collision_Mesh)

4.  **SAGE-3D VLN Data**: Navigation trajectories and instructions  
    β†’ [spatialverse/SAGE-3D_VLN_Data](https://huggingface.co/datasets/spatialverse/SAGE-3D_VLN_Data)

---

## πŸ“„ License

This dataset is released under CC-BY-NC-4.0.

---

## 🀝 Acknowledgments

Format conversion was performed using NVIDIA's [3DGRUT library](https://github.com/nv-tlabs/3dgrut). We thank the NVIDIA Toronto AI Lab for developing and open-sourcing this excellent tool.

---

## πŸ“œ Citation

If you use SAGE-3D InteriorGS USDZ in your research, please cite:

**Our Paper:**
```bibtex
@misc{miao2025physicallyexecutable3dgaussian,
  title={Towards Physically Executable 3D Gaussian for Embodied Navigation}, 
  author={Bingchen Miao and Rong Wei and Zhiqi Ge and Xiaoquan sun and Shiqi Gao and Jingzhe Zhu and Renhan Wang and Siliang Tang and Jun Xiao and Rui Tang and Juncheng Li},
  year={2025},
  eprint={2510.21307},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2510.21307}, 
}
```

Please also cite the InteriorGS dataset:
```bibtex
@misc{InteriorGS2025,
  title        = {InteriorGS: A 3D Gaussian Splatting Dataset of Semantically Labeled Indoor Scenes},
  author       = {SpatialVerse Research Team, Manycore Tech Inc.},
  year         = {2025},
  howpublished = {\url{https://huggingface.co/datasets/spatialverse/InteriorGS}}
}
```

---


<div align="center">
  <strong>SAGE-3D: Semantically and Physically-Aligned Gaussian Environments for 3D Navigation</strong>
</div>