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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
View author website
Task
Object Detection
Annotation Types
Bounding Boxes
1510000
Items
18
Classes
4372
Labels
Models using this dataset
Last updated on 
October 31, 2023
Licensed under 
Research Only
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