JHU-CROWD++
2D Box
Person
|...
许可协议: Custom

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}
}

License

Custom

数据概要
数据格式
Image,
数据量
4.372K
文件大小
2.87GB
发布方
JHU-VIU lab
The Vision & Image Understanding (VIU) Lab is a part of the Electrical and Computer Engineering department in Johns Hopkins University. We focus on several theoretical and application aspects of computer vision and image understanding.
数据集反馈
| 307 | 数据量 4.372K | 大小 2.87GB
JHU-CROWD++
2D Box
Person
许可协议: Custom

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}
}

License

Custom

数据集反馈
0
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