dataset_info:
features:
- name: image
dtype: image
- name: label
dtype: int64
- name: class_name
dtype: string
- name: file_name
dtype: string
splits:
- name: train
num_bytes: 39977866160.901
num_examples: 3671021
download_size: 32804935831
dataset_size: 39977866160.901
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
license: mit
task_categories:
- face-recognition
- image-classification
MS-Celeb-1M-v1c Dataset
This repository hosts the MS-Celeb-1M-v1c dataset, a cleaned version of the MS-Celeb-1M dataset specifically designed for face recognition tasks. It is integrated and utilized within the DORAEMON: A Unified Library for Visual Object Modeling and Representation Learning at Scale framework.
The dataset comprises over 70,000 unique identities and approximately 3.6 million images. It has been validated using the Labeled Faces in the Wild (LFW) benchmark, ensuring its quality and relevance for training robust face recognition models. This dataset offers a scalable foundation for rapid experimentation in visual recognition and representation learning.
Paper: DORAEMON: A Unified Library for Visual Object Modeling and Representation Learning at Scale Code: https://github.com/wuji3/DORAEMON
Citation
If you find this dataset or the DORAEMON project useful for your research or development, please cite the following paper:
@misc{du2025visual,
title={DORAEMON: A Unified Library for Visual Object Modeling and Representation Learning at Scale},
author={Ke Du and Yimin Peng and Chao Gao and Fan Zhou and Siqiao Xue},
year={2025},
journal={arXiv preprint arXiv:2511.04394},
url={https://arxiv.org/abs/2511.04394},
}