JHU-CROWD++
Introduced by Sindagi et al. in JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method
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
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JHU-CROWD++
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EffCC-Lite0.5
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Papers
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