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---
dataset_info:
features:
- name: file_name
dtype: string
- name: image
dtype: image
- name: refs
sequence: string
- name: mt
dtype: string
- name: human_score
dtype: float64
splits:
- name: train
num_bytes: 4783117925.25
num_examples: 26382
- name: valid
num_bytes: 593047697.75
num_examples: 3298
- name: test
num_bytes: 595467629.75
num_examples: 3298
download_size: 5956104723
dataset_size: 5971633252.75
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
- split: test
path: data/test-*
---
# Nebula Dataset
[ACCV 2024] DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioning
[](https://arxiv.org/abs/2409.19255)
[](https://github.com/Ka2ukiMatsuda/DENEB)
## Usage
```python
>>> from datasets import load_dataset
>>> nebula = load_dataset("Ka2ukiMatsuda/Nebula")
>>> print(nebula)
DatasetDict({
train: Dataset({
features: ['file_name', 'image', 'refs', 'mt', 'human_score'],
num_rows: 26382
})
valid: Dataset({
features: ['file_name', 'image', 'refs', 'mt', 'human_score'],
num_rows: 3298
})
test: Dataset({
features: ['file_name', 'image', 'refs', 'mt', 'human_score'],
num_rows: 3298
})
})
```
## Citation
```bash
@inproceedings{matsuda2024deneb,
title={DENEB: A Hallucination-Robust Automatic Evaluation Metric for Image Captioning},
author={Kazuki Matsuda and Yuiga Wada and Komei Sugiura},
booktitle={Proceedings of the Asian Conference on Computer Vision (ACCV)},
year={2024},
pages={3570--3586}
}
```
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