| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - image-classification |
| tags: |
| - 3d-gaussian-splatting |
| - data-poisoning |
| - poison-splat |
| - benchmark |
| pretty_name: TextureBench-3DGS |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # TextureBench-3DGS |
|
|
| > **Note.** This is an anonymised copy of the benchmark released for the double-blind review process. It contains no author |
| > information; the full release with attribution, licence details and accompanying code will be published after the review. |
|
|
| TextureBench-3DGS is a benchmark of **28 real outdoor scenes with dense natural texture** (gravel, grass, leaves, brick, concrete, |
| tiles, foliage), each captured as a multi-view photo set suitable for 3D Gaussian Splatting (3DGS), together with a |
| **Poison-Splat poisoned twin** of every scene. Clean scenes are high-frequency by nature, so they stress detectors that rely on a |
| high-frequency or anisotropy prior to recognise Poison-Splat inputs. The benchmark is meant for *evaluating* detectors and |
| purifiers; it was never used to train or calibrate any detector reported alongside it. |
|
|
| ## Layout |
|
|
| ``` |
| TextureBench/ |
| `-- <scene_id>/ |
| |-- clean/ |
| | |-- images/ # Clean views |
| | |-- sparse/0/ # COLMAP reconstruction |
| | `-- config.yaml # Capture and preprocessing |
| `-- ps_eps16/ |
| |-- images/ # Poisoned views |
| |-- sparse/0/ # COLMAP reconstruction |
| `-- config.yaml # Source images, attack parameters, generation settings |
| ``` |
|
|
| 28 scenes, the same file names in `clean/images` and `ps_eps16/images`. |
|
|
| ### `clean/` |
|
|
| * `images/`: the released clean views. EXIF removed. **These are the images detectors are scored on.** |
| * `sparse/0/`: COLMAP model (`cameras.bin`, `images.bin`, `points3D.bin`). |
|
|
| To train a 3DGS model on the clean scene, follow the standard 3DGS `convert.py` route, i.e. undistort first: |
|
|
| ```bash |
| colmap image_undistorter --image_path <scene>/clean/images --input_path <scene>/clean/sparse/0 \ |
| --output_path <scene>/clean_undistorted --output_type COLMAP |
| python train.py -s <scene>/clean_undistorted -r -1 |
| ``` |
|
|
| ### `ps_eps16/` |
| |
| * `images/`: the Poison-Splat poisoned views, exactly as emitted by the attacker (bounded attack, ε = 16/255, 12 000 attack |
| iterations, proxy model = the clean 3DGS reconstruction). **These are the images detectors are scored on for the poisoned class.** |
| * `sparse/0/`: COLMAP model (`cameras.bin`, `images.bin`, `points3D.bin`). |
| |
| ## Loading |
| |
| ```python |
| from huggingface_hub import snapshot_download |
| root = snapshot_download(repo_id="anonymous-user-submission/TextureBench-3DGS", repo_type="dataset") |
| ``` |
| |
| ## Privacy and licence |
| |
| All images are original captures of public outdoor spaces; no people are the subject of any view and EXIF metadata (device, |
| location) has been stripped. Released under CC BY-NC 4.0 for research use. |
| |
