Datasets:
File size: 1,396 Bytes
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---
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",
}
```
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