---
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",
}
```