README.md

metadata

dataset_info:
  features:
    - name: url
      dtype: string
    - name: query
      dtype: string
    - name: annotation
      dtype: string
  splits:
    - name: train
      num_bytes: 1887677
      num_examples: 9459
    - name: valid
      num_bytes: 250315
      num_examples: 1251
    - name: test
      num_bytes: 1186561
      num_examples: 6246
    - name: test_refer
      num_bytes: 1136787
      num_examples: 6000
  download_size: 1997128
  dataset_size: 4461340
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: valid
        path: data/valid-*
      - split: test
        path: data/test-*
      - split: test_refer
        path: data/test_refer-*
task_categories:
  - image-to-text
language:
  - en
tags:
  - Image Captioning
  - 360-degree
size_categories:
  - 1K<n<10K

Citation information

@inproceedings{maeda-etal-2023-query,
    title = "Query-based Image Captioning from Multi-context 360$cdegree$ Images",
    author = "Maeda, Koki  and
      Kurita, Shuhei  and
      Miyanishi, Taiki  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2023",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-emnlp.463",
    doi = "10.18653/v1/2023.findings-emnlp.463",
    pages = "6940--6954",
}