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Spatio-temporal interaction model for crowd video analysis
The proposed framework for analyzing medium dense crowd videos at various levels. -
UCSD dataset
The UCSD dataset is a benchmark for the analysis of abnormal detection and localization in crowded scenes. -
ShanghaiTech PartA and PartB
ShanghaiTech PartA and PartB datasets for crowd counting and localization. -
UMN dataset
The UMN dataset consists of three different crowd scenes, and the dataset has 11 videos from these scenes, with a resolution of 240 × 320. Each video sequence represents a... -
JHU-Crowd++
The dataset contains images of crowds with varying densities and sizes. -
Focal Inverse Distance Transform Maps for Crowd Localization
The proposed FIDT map is a non-overlap map, which utilizes local maxima to represent the head's center. -
Multi-source multi-scale counting in extremely dense crowd images
The UCF CC 50 dataset contains 50 images collected from publicly available web images. -
ShanghaiTech Part B
ShanghaiTech Part B is a crowd counting dataset that contains 400 training images and 316 test images. -
ShanghaiTech Part A
ShanghaiTech Part A is a crowd counting dataset that contains 300 training images and 182 test images. -
NWPU-Crowd
Crowd localization is a new computer vision task, evolved from crowd counting. Different from the latter, it provides more precise location information for each instance, not... -
ShanghaiTech
The ShanghaiTech dataset includes 330 training and 107 test videos recorded at 13 different background locations.
