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JHU-CROWD++
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Jun 28, 2021 3:54 AM
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dataset

Overview

A large-scale unconstrained crowd counting dataset.

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.

Citation

Please use the following citation when referencing the dataset:

@inproceedings{sindagi2019pushing,
title={Pushing the frontiers of unconstrained crowd counting: New dataset and benchmark method},
author={Sindagi, Vishwanath A and Yasarla, Rajeev and Patel, Vishal M},
booktitle={Proceedings of the IEEE International Conference on Computer Vision},
pages={1221--1231},
year={2019}
}
@article{sindagi2020jhu-crowd++,
title={JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method},
author={Sindagi, Vishwanath A and Yasarla, Rajeev and Patel, Vishal M},
journal={Technical Report},
year={2020}
}
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数据集信息
应用场景Person
标注类型Box2DClassification
任务类型暂无
LicenseCustom
更新时间2021-03-24 23:24:07
数据概要
数据格式Image
数据数量4.37K
已标注数量5972
文件大小3GB
版权归属方
JHU-VIU lab
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