PASS: Pictures without humAns for Self-Supervised Pretraining

TL;DR: An ImageNet replacement dataset for self-supervised pretraining without humans

Content

PASS is a large-scale image dataset that does not include any humans, human parts, or other personally identifiable information that can be used for high-quality pretraining while significantly reducing privacy concerns.

Download the dataset

Generally: all information is on our webpage.

For downloading the dataset, please visit our dataset on zenodo. There you can download it in tar files and find the meta-data.

You can also download the images from their AWS urls, from here.

Pretrained models

Contribute your models

Please let us know if you have a model pretrained on this dataset and I will add this to the list above.

Citation

@Article{asano21pass,
author = "Yuki M. Asano and Christian Rupprecht and Andrew Zisserman and Andrea Vedaldi",
title = "PASS: An ImageNet replacement for self-supervised pretraining without humans",
journal = "NeurIPS Track on Datasets and Benchmarks",
year = "2021"
}