| --- |
| license: other |
| tags: |
| - 3d-gaussian-splatting |
| - 3dgs |
| - computer-vision |
| - 3d-reconstruction |
| - object-centric |
| - multi-view |
| - colmap |
| - transparency-evaluation |
| - noise-infill |
| --- |
| |
| # Noise Guided Splatting (NGS) Transparency Datasets |
|
|
| [GitHub](https://github.com/OpsiClear/noise_guided_splatting) | [Project Page](https://opsiclear.github.io/ngs/) |
|
|
| This repository contains the datasets used in the paper **"Fix False Transparency by Noise Guided Splatting"**. It is designed to facilitate research and benchmarking for the "false transparency" artifact in 3D Gaussian Splatting (3DGS) reconstructions of opaque objects. |
|
|
| The repository is composed of four distinct subsets, each augmented with noise Gaussian infills (`inside_gaussians.ply`) crucial for evaluating surface opacity. |
|
|
| ## Dataset Description |
|
|
| The collection includes two original high-resolution datasets (`stones` and `objects`) and two augmented subsets from popular benchmarks (`DTU` and `OmniObject3D`). The primary purpose is to provide data exhibiting pronounced transparency issues and the necessary tools (noise infills) to quantify them using our proposed **Surface Opacity Score (SOS)** metric. |
|
|
| ### Subsets |
|
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| 1. **Stones**: A high-resolution object-centric dataset of over 100 stone specimens, captured with complex geometries and textures to challenge reconstruction robustness. |
| 2. **Objects**: A supplementary dataset featuring a mixture of everyday objects with diverse material properties. |
| 3. **DTU**: An augmented subset of the [DTU Robot Image Data Set](http://roboimagedata.compute.dtu.dk/?page_id=36), with noise infills generated to evaluate transparency on these standard benchmarks. |
| 4. **OmniObject3D**: An augmented subset of the [OmniObject3D Dataset](https://omniobject3d.github.io/), similarly complemented with noise infills. |
|
|
| ## Dataset Structure |
|
|
| The dataset is organized into four main directories, one for each subset. Each scan within these directories follows a consistent structure: |
|
|
| ``` |
| |
| . |
| ├── stones/ |
| │ ├── scan\_*/ |
| │ │ ├── images/ |
| │ │ ├── masks/ |
| │ │ ├── sparse/0/ |
| │ │ ├── inside_gaussians.ply \# Noise Gaussians for evaluation |
| │ │ └── surface_gaussians.ply \# Reconstructed surface Gaussians |
| │ └── ... |
| ├── objects/ |
| │ ├── scan\_*/ |
| │ │ └── ... |
| ├── DTU/ |
| │ ├── scan\_*/ |
| │ │ └── ... |
| └── OmniObject3D/ |
| ├── scan\_*/ (e.g., antique\_004, dinosaur\_004) |
| │ └── ... |
| |
| ```` |
|
|
| ## Usage |
|
|
| This dataset is designed to be used with the Hugging Face `datasets` library, which can load each subset using a specific configuration name. |
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| To evaluate transparency using our method, see the official [NGS repository](https://github.com/OpsiClear/noise_guided_splatting) |
|
|
|
|
| ## Licensing |
|
|
| This dataset is released under a mixed license scheme: |
|
|
| * The **`stones`** and **`objects`** datasets are original works and are released under the **[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)** license. |
| * The generated **noise infill files (`inside_gaussians.ply`)** for all subsets, including `DTU` and `OmniObject3D`, are also released under **CC BY 4.0**. |
| * The image and COLMAP data in the **`DTU`** and **`OmniObject3D`** subsets are provided here as derived works for convenience. They remain subject to their original licenses. Please consult the original dataset pages for specific licensing details. |
| |
| ## Citation |
| |
| If you use this dataset or the NGS methodology in your research, please cite our paper: |
| |
| ```bibtex |
| @inproceedings{ElHakie2025NGS, |
| author = {El Hakie, Aly and Lu, Yiren and Yin, Yu and Jenkins, Michael and Liu, Yehe}, |
| title = {Fix False Transparency by Noise Guided Splatting}, |
| booktitle = {The Thirty-ninth Annual Conference on Neural Information Processing Systems}, |
| year = {2025} |
| } |
| ``` |
| |
