OpenScan / README.md
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---
license: other
language:
- en
task_categories:
- text-classification
- image-segmentation
pretty_name: OpenScan
size_categories:
- 10K<n<100K
tags:
- 3d-scene-understanding
- open-vocabulary
- scannet200
- benchmark
- aaaai-2026
---
# OpenScan
OpenScan is a benchmark for generalized open-vocabulary 3D scene understanding. It extends ScanNet200-style scene understanding with eight object-attribute aspects: material, affordance, property, type, manner, synonyms, requirement, and element.
This dataset mirror contains the OpenScan validation annotations and evaluation ground-truth files for the AAAI 2026 paper.
## Files
| File | Description |
| --- | --- |
| `openscan_val_raw.json` | Raw validation annotations with one record per scene object. |
| `openscan_label_mapping/` | Expanded TSV label mappings for all eight OpenScan aspects. |
| `openscan_val_gt/` | Processed validation ground-truth files for evaluation. |
The raw validation JSON contains 10,388 annotated objects from 312 validation scenes. The processed ground truth contains 312 scene files for each of the eight OpenScan aspects.
## Annotation Format
Each raw annotation record has this structure:
```json
{
"scene_id": "scene0011_00",
"object_id": "0",
"object_name": "floor",
"material": "stone",
"affordance": "stand",
"property": "other",
"type": "land",
"manner": "other",
"synonyms": "other",
"requirement": "other",
"element": "other"
}
```
## Usage
Load the raw validation annotation table with `datasets`:
```python
from datasets import load_dataset
dataset = load_dataset(
"json",
data_files="hf://datasets/garrying/OpenScan/openscan_val_raw.json",
split="train",
)
```
Download the processed validation ground truth for evaluation:
```bash
hf download garrying/OpenScan --repo-type dataset --local-dir . --include "openscan_val_gt/**"
```
The `openscan_val_gt/` directory contains:
```text
gt_affordance/
gt_element/
gt_manner/
gt_material/
gt_property/
gt_requirement/
gt_synonyms/
gt_type/
```
## Project
- Project page: https://youjunzhao.github.io/OpenScan/
- Code and evaluation: https://github.com/YoujunZhao/OpenScan
- Paper: https://arxiv.org/abs/2408.11030
## Citation
```bibtex
@article{zhao2024openscan,
title={OpenScan: A Benchmark for Generalized Open-Vocabulary 3D Scene Understanding},
author={Zhao, Youjun and Lin, Jiaying and Ye, Shuquan and Pang, Qianshi and Lau, Rynson WH},
journal={arXiv preprint arXiv:2408.11030},
year={2024}
}
```