About
In this repository, we gather a collection of images featuring people, both labelled and unlabelled. The primary objective of this dataset is to serve as training data for self-supervised models that focus on recognizing individuals within the images. Using this trained model, it becomes possible to tackle a range of related tasks with limited labelled data, including human pose estimation, human segmentation, human classification, human activity recognition, and human object detection.
18 commits
2 contributors
20 downloads
22 gb
2 stars
Repository contents
65K image files > 99%
5 text files < 1%
