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PASS

An ImageNet replacement for self-supervised pretraining without humans

PASS

PASS is a large-scale image dataset that does not include any humans and which can be used for high-quality pretraining while significantly reducing privacy concerns.

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Visual Geometry Group, University of Oxford
https://www.robots.ox.ac.uk/~vgg/
Task
Image Classification
Annotation Types
Classification Tags
6000000
Items
20000
Classes
6000000
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
CC-BY
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