Initial upload: 4 packed scenes + 541-question benchmark

.gitattributes

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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+paper.pdf filter=lfs diff=lfs merge=lfs -text
+scenes/book-nook/book-nook.blend filter=lfs diff=lfs merge=lfs -text
+scenes/city-street/city-street.blend filter=lfs diff=lfs merge=lfs -text
+scenes/postwar-city/postwar-city.blend filter=lfs diff=lfs merge=lfs -text
+scenes/whitechapel/whitechapel.blend filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: cc-by-nc-4.0
+language:
+  - en
+tags:
+  - robotics
+  - vision-language
+  - human-robot-interaction
+  - ptz-camera
+  - benchmark
+  - blender
+size_categories:
+  - n<1K
+task_categories:
+  - visual-question-answering
+  - image-classification
+  - object-detection
+pretty_name: SCOPE — A Real-Time Natural Language Camera Agent Benchmark
+---
+
+# SCOPE Benchmark
+
+The SCOPE benchmark accompanies the HRI '26 paper [*SCOPE: A Real-Time Natural Language Camera Agent at the Edge*](https://doi.org/10.1145/3757279.3785641). It evaluates modular multimodal agentic systems controlling PTZ cameras in simulated and physical settings.
+
+## Contents
+
+- **scenes/** — 4 Blender `.blend` scenes (with packed textures where the original assets were available):
+  - `whitechapel/whitechapel.blend` — French Quarter exterior, ~95% textured
+  - `book-nook/book-nook.blend` — small interior, geometry-only (original SL/MySims textures lost)
+  - `city-street/city-street.blend` — urban scene, geometry-only (re-download CC0 textures via `scripts/fetch_textures/`)
+  - `postwar-city/postwar-city.blend` — partial textures, ~35% textured
+- **scope_541.csv** — 541-question benchmark with columns: `question_id`, `file_location`, `question`, `expected_answer`, `eval_category`, `difficulty`, `multi_step_mode`, `required_tools_policy`, `expected_tool_order_json`, `evaluation_notes`.
+
+## Task categories
+
+8 categories (see paper §4):
+1. Object identification
+2. Object counting
+3. Spatial reasoning
+4. Multi-step planning
+5. Camera control validation
+6. Perception robustness
+7. Error recovery
+8. Tool-use correctness
+
+## Usage
+
+```bash
+pip install huggingface_hub
+huggingface-cli download HindsboNikolaj/scope-benchmark \
+    --repo-type dataset \
+    --local-dir benchmark/
+```
+
+Then run the benchmark from the [main repository](https://github.com/HindsboNikolaj/SCOPE):
+
+```bash
+git clone https://github.com/HindsboNikolaj/SCOPE
+cd SCOPE
+bash scripts/01_install.sh
+bash scripts/run_eval_pipeline.sh
+```
+
+## Texture state
+
+Two of the four scenes (`book-nook`, `city-street`) shipped without textures from their original authors — they referenced absolute Windows paths (`D:/SL/...`, `E:/New folder/...`) that were never bundled. The packed `.blend` files in this dataset are honest about what's available:
+
+| Scene | Texture refs | Packed | Missing |
+|---|---|---|---|
+| whitechapel | 193 | 188 (97%) | 5 (paid HDR addon) |
+| book-nook | 385 | 0 | 296 (SL/MySims rips) |
+| city-street | 127 | 0 | 126 (CC0 — re-downloadable) |
+| postwar-city | 71 | 25 (35%) | 46 (mixed sources) |
+
+To restore textures for the partially-bundled scenes, see [`docs/MISSING_TEXTURES.md`](https://github.com/HindsboNikolaj/SCOPE/blob/main/docs/MISSING_TEXTURES.md) in the main repo — there's an automated AmbientCG downloader and a manifest of where to find the rest.
+
+The benchmark questions are designed to be answerable from geometry alone for most rows, so even untextured scenes produce meaningful results.
+
+## License
+
+The dataset is released under CC-BY-NC-4.0 for research use. Individual scene assets retain their original licenses — see the per-scene README in each subfolder for source attribution.
+
+## Citation
+
+```bibtex
+@inproceedings{hindsbo2026scope,
+  title={SCOPE: A Real-Time Natural Language Camera Agent at the Edge},
+  author={Hindsbo, Nikolaj and Ehsani, Sina and Mishra, Pragyana},
+  booktitle={Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction (HRI '26)},
+  year={2026},
+  publisher={ACM},
+  doi={10.1145/3757279.3785641}
+}
+```

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