File size: 1,984 Bytes
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license: mit
dataset_info:
features:
- name: img
dtype: image
- name: question
dtype: string
- name: choices
dtype: string
- name: answer_0
dtype: string
- name: answer_1
dtype: string
- name: answer_2
dtype: string
- name: answer_3
dtype: string
- name: answer_4
dtype: string
- name: gt
dtype: string
- name: avg_rating
dtype: float64
- name: category
dtype: int64
splits:
- name: bounding_box
num_bytes: 3981007.0
num_examples: 36
- name: non_bounding_box
num_bytes: 9377519.0
num_examples: 76
download_size: 7697970
dataset_size: 13358526.0
configs:
- config_name: default
data_files:
- split: non_bounding_box
path: data/non_bounding_box-*
- split: bounding_box
path: data/bounding_box-*
---
This is the visual human preferences dataset with both the bounding-box and non-bounding-box variants from the paper "A Dataset for Dynamic Human Preferences for Vision Language Models".
## Data Attribution
Images in this benchmark dataset are sourced from the [Visual Genome Dataset (Version 1.2)](https://homes.cs.washington.edu/~ranjay/visualgenome/index.html). Images were modified to include bounding boxes.
- The Visual Genome dataset is licensed under [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/)
The original Visual Genome Dataset was introduced in:
```bibtex
@article{krishna2017visual,
title={Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations},
author={Ranjay Krishna and Yuke Zhu and Oliver Groth and Justin Johnson and Kenji Hata and Joshua Kravitz and Stephanie Chen and Yannis Kalantidis and Li-Jia Li and David A. Shamma and Michael S. Bernstein and Li Fei-Fei},
journal={International Journal of Computer Vision},
year={2017},
volume={123},
pages={32-73},
url={https://doi.org/10.1007/s11263-016-0981-7},
doi={10.1007/s11263-016-0981-7}
}
``` |