---
license: mit
language:
  - en
pretty_name: Mesh2QA ScanNet 3D Question Answering
task_categories:
  - question-answering
tags:
  - 3d
  - visual-question-answering
  - scannet
  - mesh2qa
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: trainval.jsonl
      - split: test
        path: test.jsonl
---

# 3D Question Answering ScanNet Export

This dataset card publishes a Hugging Face Dataset Viewer-ready JSONL export for the
[3D Question Answering](https://shuquanye.com/3DQA_website/) project by Shuquan Ye,
Dongdong Chen, Songfang Han, and Jing Liao.

Related links:

- [Project page](https://shuquanye.com/3DQA_website/)
- [arXiv](https://arxiv.org/abs/2112.08359v2)
- [Code](https://github.com/pleaseconnectwifi/3DQA)
- [Dataset repository](https://huggingface.co/datasets/pleaseconnectwifi/3DQA)

## Splits

- `train`: 9160 examples from `scene0000_00` through `scene0706_00`; this intentionally combines the original train and validation portion. Because some cloud files were lost, the train and validation split cannot be distinguished.
- `test`: 902 examples from `scene0707_00` through `scene0806_00`.

The split keeps the current project convention of using the ScanNet test scene block separately while publishing train and validation together.

## Fields

- `id`, `qakey`: example identifiers.
- `scene_id`: ScanNet scene identifier.
- `question_id`, `question`, `question_status`: question metadata.
- `perspective_specific`, `camera`: viewpoint metadata for the question.
- `answers`, `answer_confidences`, `answer_annotations`, `has_answer`: answer data and annotations.
- `source`: original source metadata.

## Citation

If you use this dataset, please cite the original 3DQA paper:

```bibtex
@article{ye20213dqa,
  title = {3D Question Answering},
  author = {Ye, Shuquan and Chen, Dongdong and Han, Songfang and Liao, Jing},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  doi = {10.48550/arXiv.2112.08359},
}
```