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Diffuse-Denoise-Count: Accurate Crowd-Counting with Diffusion Models
Crowd counting is a key aspect of crowd analysis and has been typically accomplished by estimating a crowd-density map and summing over the density values. -
Crowd Counting Datasets
The dataset used in the paper for crowd counting, which includes five challenging benchmarks: ShanghaiTech Part A & Part B (SHHA & SHHB), UCF-QNRF (QNRF), JHU-Crowd++... -
A survey of recent advances in CNN-based single image crowd counting and dens...
The WorldExpo’10 dataset contains 199,923 pedestrians labeled at their centers of heads. -
Attention to Head Locations for Crowd Counting
The proposed method is conducted on 3 highly challenging publicly datasets: ShanghaiTech, UCF CC 50 and WorldExpo’10. -
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 B
The ShanghaiTech B dataset contains images of people in unconstrained crowded scenes. -
ShanghaiTech A
The ShanghaiTech A dataset contains images of people in unconstrained crowded scenes. -
VisDrone2019 Vehicle
The VisDrone2019 Vehicle dataset contains images of vehicles in unconstrained crowded scenes. -
VisDrone2019 People & Vehicle
The VisDrone2019 People & Vehicle dataset contains images of people and vehicles in unconstrained crowded scenes. -
Crowd Counting on Images with Scale Variation and Isolated Clusters
Crowd counting is to estimate the number of objects in an image of unconstrained congested scenes. Designing a general crowd counting algorithm applicable to a wide range of...
