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Crowd Counting datasets
archive 2025-07-28
23 datasets carry the task tag "Crowd Counting" (the task itself: Crowd Counting), ordered by the archive's paper count. Page 1 of 1: 23 shown of 23. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Crowd Counting datasets 1–23 of 23
The Shanghaitech dataset is a large-scale crowd counting dataset.
277 papers · 5 benchmarks
The UCF-QNRF dataset is a crowd counting dataset and it contains large diversity both in scenes, as well as in background types.
176 papers · 1 benchmark
JHU-CROWD++ is A large-scale unconstrained crowd counting dataset with 4,372 images and 1.51 million annotations.
48 papers · 1 benchmark
NWPU-Crowd consists of 5,109 images, in a total of 2,133,375 annotated heads with points and boxes.
32 papers · 2 benchmarks
UCF-CC-50 is a dataset for crowd counting and consists of images of extremely dense crowds.
32 papers · 0 benchmarks
(JHU-CROWD) a crowd counting dataset that contains 4,250 images with 1.11 million annotations.
22 papers · 0 benchmarks
FDST (Fudan-ShanghaiTech)
The Fudan-ShanghaiTech dataset (FDST) is a dataset for video crowd counting.
18 papers · 0 benchmarks
Datasets for multi-view crowd counting in wide-area scenes.
12 papers · 1 benchmark
CVCS (Cross-View Cross-Scene Multi-View Crowd Counting Dataset)
CVCS is a synthetic multi-view people dataset, containing 31 scenes, where 23 are for training and the rest 8 for testing.
10 papers · 1 benchmark
The DLR-ACD dataset is a collection of aerial images for crowd counting and density estimation, as well as for person localization at mass events.
6 papers · 1 benchmark
DroneCrowd is a benchmark for object detection, tracking and counting algorithms in drone-captured videos.
6 papers · 0 benchmarks
Includes 4405 images with 111251 heads annotated.
6 papers · 0 benchmarks
WWW Crowd provides 10,000 videos with over 8 million frames from 8,257 diverse scenes, therefore offering a comprehensive dataset for the area of crowd understanding.
5 papers · 0 benchmarks
The TUB CrowdFlow is a synthetic dataset that contains 10 sequences showing 5 scenes.
4 papers · 0 benchmarks
The newly introduced UP-COUNT dataset includes drone footage captured with cameras from the DJI Mini 2 family UAV.
3 papers · 1 benchmark
BEV Crowd-Counting dataset extended from CityUHK-X
2 papers · 0 benchmarks
Multi Task Crowd is a new 100 image dataset fully annotated for crowd counting, violent behaviour detection and density level classification.
2 papers · 0 benchmarks
RSOC (Remote Sensing Object Counting)
RSOC is a large-scale object counting dataset with remote sensing images, which contains four important geographic objects: buildings, crowded ships in harbors, large-vehicles and small-vehicles in parking lots.
2 papers · 0 benchmarks
SmartCity consists of 50 images in total collected from ten city scenes including office entrance, sidewalk, atrium, shopping mall etc..
2 papers · 0 benchmarks
A large synthetic multi-camera crowd counting dataset with a large number of scenes and camera views to capture many possible variations, which avoids the difficulty of collecting and annotating such a large real dataset.
1 paper · 0 benchmarks
人群计数旨在识别物体的数量，在智能交通、城市管理和安全监控中发挥着重要作用。由于比例变化、照明变化、遮挡和较差的成像条件，尤其是在夜间和雾霾条件下，人群计数的任务非常具有挑战性。 在本文中，我们提出了一个基于无人机的 RGB-Thermal 人群计数数据集 （DroneRGBT），该数据集由 3600…
1 paper · 1 benchmark
This dataset is an extremely challenging set of over 3000+ original Crowd images captured and crowdsourced from over 300+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at…
0 papers · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.