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JHU-CROWD++

A large-scale unconstrained crowd counting dataset

JHU-CROWD++

A comprehensive dataset with 4,372 images and 1.51 million annotations. In comparison to existing datasets, the proposed dataset is collected under a variety of diverse scenarios and environmental conditions. In addition, the dataset provides comparatively richer set of annotations like dots, approximate bounding boxes, blur levels, etc.

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JHU-VIU lab
https://engineering.jhu.edu/vpatel36/
Task
Object Detection
Annotation Types
Bounding Boxes
1510000
Items
18
Classes
4372
Labels
Models using this dataset
Last updated on 
January 20, 2022
Licensed under 
Research Only
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