metadata

license: apache-2.0
task_categories:
  - visual-question-answering
language:
  - ja
size_categories:
  - 1K<n<10K

JIC-VQA

Dataset Description

Japanese Image Classification Visual Question Answering (JIC-VQA) is a benchmark for evaluating Japanese Vision-Language Models (VLMs). We built this benchmark based on the recruit-jp/japanese-image-classification-evaluation-dataset by adding questions to each sample. All questions are multiple-choice, each with four options. We select options that closely relate to their respective labels in order to increase the task's difficulty.

The images include 101 types of Japanese food, 30 types of Japanese flowers, 20 types of Japanese facilities, and 10 types of Japanese landmarks.

Uses

All the images in this dataset are licensed under CC-BY-2.0, CC-BY-NC-2.0, Public Domain Mark 1.0, or Public Domain Dedication. Please note that CC-BY-NC-2.0 prohibits commercial use. Also, CC-BY-2.0, CC-BY-NC-2.0, and Public Domain Mark 1.0 prohibit sublicensing, so the collected image data cannot be published.

Citation

@misc{jic-vqa,
    title={Japanese Image Classification Visual Question Answering (JIC-VQA) Dataset},
    author={Mikihiro Tanaka and Peifei Zhu and Shuhei Yokoo}
    url={https://huggingface.co/line-corporation/JIC-VQA},
}