Approaches on crowd counting and density estimation: a review
In recent years, urgent needs for counting crowds and vehicles have greatly promoted
research of crowd counting and density estimation. Benefiting from the rapid development of …
research of crowd counting and density estimation. Benefiting from the rapid development of …
Cnn-based density estimation and crowd counting: A survey
Accurately estimating the number of objects in a single image is a challenging yet
meaningful task and has been applied in many applications such as urban planning and …
meaningful task and has been applied in many applications such as urban planning and …
Counting varying density crowds through density guided adaptive selection CNN and transformer estimation
In real-world crowd counting applications, the crowd densities in an image vary greatly.
When facing density variation, humans tend to locate and count the targets in low-density …
When facing density variation, humans tend to locate and count the targets in low-density …
Dr. vic: Decomposition and reasoning for video individual counting
Pedestrian counting is a fundamental tool for understanding pedestrian patterns and crowd
flow analysis. Existing works (eg, image-level pedestrian counting, crossline crowd counting …
flow analysis. Existing works (eg, image-level pedestrian counting, crossline crowd counting …
Adversarial learning for multiscale crowd counting under complex scenes
Y Zhou, J Yang, H Li, T Cao… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
In this article, a multiscale generative adversarial network (MS-GAN) is proposed for
generating high-quality crowd density maps of arbitrary crowd density scenes. The task of …
generating high-quality crowd density maps of arbitrary crowd density scenes. The task of …
VisDrone-CC2021: the vision meets drone crowd counting challenge results
Crowding counting research evolves quickly by the leverage of development in deep
learning. Many researchers put their efforts into crowd counting tasks and have achieved …
learning. Many researchers put their efforts into crowd counting tasks and have achieved …
SCLNet: Spatial context learning network for congested crowd counting
Accurate congested crowd counting is a challenging task, especially in complex crowd
scenes. Many existing counting models easily fail in such cases. To solve this problem, we …
scenes. Many existing counting models easily fail in such cases. To solve this problem, we …
Weakly Supervised Video Individual Counting
Abstract Video Individual Counting (VIC) aims to predict the number of unique individuals in
a single video. Existing methods learn representations based on trajectory labels for …
a single video. Existing methods learn representations based on trajectory labels for …
Spatial-temporal graph network for video crowd counting
In recent years, researchers have developed many deep-learning-based methods to count
crowd numbers in static images. However, much fewer works focus on video-based crowd …
crowd numbers in static images. However, much fewer works focus on video-based crowd …
CACrowdGAN: Cascaded attentional generative adversarial network for crowd counting
Crowd counting is a valuable technology for extremely dense scenes in the transportation.
Existing methods generally have higher-order inconsistencies between ground truth density …
Existing methods generally have higher-order inconsistencies between ground truth density …