Initial upload: 44 3DGS models with provenance graph labels across 5 scenes

.gitattributes

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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+*.ply filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+  - en
+task_categories:
+  - graph-ml
+  - image-feature-extraction
+tags:
+  - 3d-gaussian-splatting
+  - 3dgs
+  - provenance
+  - forensics
+  - graph
+size_categories:
+  - 1K<n<10K
+---
+
+# 3DGS Provenance Dataset
+
+This dataset accompanies the paper **GaussTrace: Provenance Analysis of 3D Gaussian Splatting Models with Evidence-based LLM Reasoning** (ICML 2026).
+
+## Description
+
+A dataset of **44 3DGS models** across 5 scenes with ground-truth directed provenance graphs, designed for evaluating 3DGS provenance analysis methods.
+
+Each scene contains an original 3DGS model and multiple derived versions obtained through common editing operations:
+
+- **Semantic edits**: appearance change (e.g., turn into Hulk, old lady, skin tone)
+- **Geometric edits**: translation, rotation, scale, crop
+- **Attribute edits**: color noise, opacity noise, rotation noise
+- **Merge**: combining two 3DGS models
+- **Composite edits**: multiple operations applied sequentially
+
+## Scenes
+
+| Scene | Source | # Models | # Edges |
+|-------|--------|----------|---------|
+| bonsai | Mip-NeRF360 | 9 | 8 |
+| counter | Mip-NeRF360 | 8 | 7 |
+| face | Instruct-NeRF2NeRF | 8 | 7 |
+| playroom | Deep Blending | 9 | 8 |
+| drjohnson | Deep Blending | 10 | 9 |
+| **Total** | | **44** | **39** |
+
+## Structure
+
+```
+3DGS_Provenance/
+├── bonsai/
+│   ├── labels.json          # Ground-truth provenance graph
+│   ├── bonsai.ply           # Original model
+│   ├── bonsai_crop.ply      # Cropped version
+│   └── ...
+├── counter/
+│   ├── labels.json
+│   └── ...
+├── face/
+│   ├── labels.json
+│   └── ...
+├── playroom/
+│   ├── labels.json
+│   └── ...
+└── drjohnson/
+    ├── labels.json
+    └── ...
+```
+
+## Label Format
+
+Each `labels.json` contains a directed provenance graph:
+
+```json
+{
+  "scene": "bonsai",
+  "nodes": ["bonsai", "bonsai_crop", ...],
+  "edges": [
+    {"source": "bonsai", "target": "bonsai_crop"},
+    ...
+  ]
+}
+```
+
+- **nodes**: list of model IDs (file path is `{id}.ply`)
+- **edges**: directed edges where `source` is the parent model and `target` is the derived model. Merge operations (e.g., playroom + teddybear → playroom_teddybear) have two incoming edges.
+
+## Citation
+
+```bibtex
+@inproceedings{han2026gausstrace,
+  author    = {Haoliang Han and Ziyuan Luo and Renjie Wan},
+  title     = {GaussTrace: Provenance Analysis of 3D Gaussian Splatting
+               Models with Evidence-based LLM Reasoning},
+  booktitle = {International Conference on Machine Learning (ICML)},
+  year      = {2026},
+}
+```
+
+## License
+
+For research purposes only.

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+    {"source": "bonsai", "target": "bonsai_blue"},
+    {"source": "bonsai", "target": "bicycle_blue"},
+    {"source": "bonsai_blue", "target": "bonsai_blue_color"},
+    {"source": "bonsai_blue", "target": "bonsai_blue_opacity"},
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