text-image pairs
FaceCaption-1M-image-text-pairs
Citation
@misc{dai202415mmultimodalfacialimagetext,
title={15M Multimodal Facial Image-Text Dataset},
author={Dawei Dai and YuTang Li and YingGe Liu and Mingming Jia and Zhang YuanHui and Guoyin Wang},
year={2024},
eprint={2407.08515},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2407.08515},
}
@article{dai2026facecaption15m,
title={FaceCaption-15M: Benchmarking and Enhancing Facial Vision-Language… See the full description on the dataset page: https://huggingface.co/datasets/OpenFace-CQUPT/FaceCaption-1M-image-text-pairs.image-text-pairs-ja-cc0-2
はじめに
このデータセットは画像生成で日本語を生成したいときに使うデータセットです。
ライセンス
CC-0です。著作権を放棄して使いやすくしました。
作り方の概要
gpt-oss-20bを使って、約8万個からなる単語集兼短文集を作りました。
その文章をPillowとPythonでランダム要素を入れながら100万枚と10万枚でレンダリングしました。
フォントはNoto Sans JPなのでライセンス的には問題ないと思います。
reevaluate-image-text-pairs
REEVLAUATE Image-Text Pair Dataset
Overview
This is an image-text pair dataset constructed for the Knowledge-Enhanced Multimodal Retrieval System, built upon the REEVLAUATE KG ArtKB.
The dataset is designed for training and evaluating the CLIP model for the retrieval system.
Data Source
The ArtKB knowledge base combines data from two primary sources:
Wikidata
Pilot Museums
Dataset Structure
The dataset is organized into three splits:
Train:… See the full description on the dataset page: https://huggingface.co/datasets/xuemduan/reevaluate-image-text-pairs.Plant-Diseases-Image-Text-Pairsimage-text-pairs-ja-cc0
Japanese Glyph Images with English Captions (CC0)
This dataset contains Japanese glyph images rendered with black text on white background.
Each .png image has a corresponding .txt file with an English caption:
This image is saying "<Japanese>". The background is white. The letter is black.
Structure
train/ — PNG images and matching TXT captions (same base filename)
provenance/assets_registry.csv — Fonts and license info
LICENSE.txt — CC0-1.0 license
Generation… See the full description on the dataset page: https://huggingface.co/datasets/alfredplpl/image-text-pairs-ja-cc0.instruct-pix2pix_image-text-pairs