Papers › NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization

NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting and Localization

10 Jan 2020arXiv:2001.03360archive 2025-07-28

Qi. Wang, Junyu. Gao, Wei. Lin, Xuelong. Li

In the last decade, crowd counting and localization attract much attention of researchers due to its wide-spread applications, including crowd monitoring, public safety, space design, etc. Many Convolutional Neural Networks (CNN) are designed for tackling this task. However, currently released datasets are so small-scale that they can not meet the needs of the supervised CNN-based algorithms. To remedy this problem, we construct a large-scale congested crowd counting and localization dataset, NWPU-Crowd, consisting of 5,109 images, in a total of 2,133,375 annotated heads with points and boxes. Compared with other real-world datasets, it contains various illumination scenes and has the largest density range (0~20,033). Besides, a benchmark website is developed for impartially evaluating the different methods, which allows researchers to submit the results of the test set. Based on the proposed dataset, we further describe the data characteristics, evaluate the performance of some mainstream state-of-the-art (SOTA) methods, and analyze the new problems that arise on the new data. What's more, the benchmark is deployed at \url{https://www.crowdbenchmark.com/}, and the dataset/code/models/results are available at \url{https://gjy3035.github.io/NWPU-Crowd-Sample-Code/}.

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gjy3035/Awesome-Crowd-Counting officialmentioned in papermentioned on GitHubpytorch report
gjy3035/NWPU-Crowd-Sample-Code officialmentioned in papermentioned on GitHubpytorch report
MagazzuGaetano/Crowd-Counting-DEMO mentioned on GitHubpytorchMIT report

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judge gjy3035/NWPU-Crowd-Sample-Code/misc/evaluation_code.py official repository ran · our draft was wrong MIT (permissive) · 7f332d3b08e57871 · report
readoutput gjy3035/NWPU-Crowd-Sample-Code/misc/evaluation_code.py official repository ran · our draft was wrong MIT (permissive) · a61a43c8b2c5e6fe · report
readtarget gjy3035/NWPU-Crowd-Sample-Code/misc/evaluation_code.py official repository ran · our draft was wrong MIT (permissive) · 32fbf464f192cf31 · report
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hungarian gjy3035/NWPU-Crowd-Sample-Code-for-Localization/eval/utils.py community (archive-listed) ran · our draft was wrong fingerprinted MIT (permissive) · 8b51984d5c6a86dd · report
make_layers MagazzuGaetano/Crowd-Counting-DEMO/models/counters/CSRNet.py community (archive-listed) ran · our draft was wrong MIT (permissive) · bd14ee2717325fe2 · report
make_res_layer MagazzuGaetano/Crowd-Counting-DEMO/models/counters/Res101.py community (archive-listed) ran MIT (permissive) · 50357b3d2ea8e365 · report
read_pred_and_gt gjy3035/NWPU-Crowd-Sample-Code-for-Localization/eval/utils.py community (archive-listed) ran MIT (permissive) · 982a72710f10d6cc · report
remove_transparency MagazzuGaetano/Crowd-Counting-DEMO/misc/utils.py community (archive-listed) ran MIT (permissive) · 9271b49f33ac9ea7 · report

Tasks

Crowd Counting

Datasets

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NWPU-Crowd

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Test

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