3DQA / README.md
pleaseconnectwifi's picture
Update cleaned 3DQA dataset
3cd2274
---
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},
}
```