Datasets › JHU-CROWD++

JHU-CROWD++

Introduced by Vishwanath A. Sindagi et al. in JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method archive 2025-07-28

JHU-CROWD++ is A large-scale unconstrained crowd counting dataset with 4,372 images and 1.51 million annotations. This 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.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Crowd Counting JHU-CROWD++ EffCC-Lite0.5 MAE 77.24 Improved Knowledge Distillation for Crowd Counting on IoT Device huangzuo/effcc_distilled 3 Compare

Papers archive 2025-07-28

3 shown of 3 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 48. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • JHU-CROWD++

1 variant name, as the archive lists them.

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