Datasets:

pleaseconnectwifi
/

3DQA

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 project by Shuquan Ye, Dongdong Chen, Songfang Han, and Jing Liao.

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:

@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},
}