To simultaneously estimate the number of heads and locate heads with bounding boxes, we
resort to detection-based crowd counting by leveraging RGB-D data and design a dual-path …

Crowd density estimation has gained significant research interest owing to its potential in
various industries and social applications. Therefore, this article proposes a multistyle joint …

Owing to the expansion in processing of industrial information through advances in machine
learning, the demand for accurate crowd counting in various applications is increasing. We …

To tackle the negative effect of the arbitrary crowd distribution on the counting task, in this
article, we propose a novel RGB-D crowd counting approach, including a cross-modal cycle …

Deep learning-based blind image deblurring plays an essential role in solving image blur
since all existing kernels are limited in modeling the real world blur. Thus far, researchers …

Albeit recent cross-modal crowd counting methods have achieved promising performance,
most of them only focus on how to combine the RGB modality and thermal modality, and …

In recent years, crowd counting has attracted widespread attention due to its enormous
potential in the public safety inspection process. Visual-based measurement techniques …

Presently, to obtain a more accurate density map and crowd number, existing methods often
count by combining training RGB images and depth images. However, these methods are …

As population growth and urbanization continue, accurate crowd counting is increasingly
important for public safety management and the Internet of Video Things (IOVT). However …

To simultaneously estimate the crowd count and the density map from the crowd images,
this paper presents a novel cross-modal fusion based approach for RGB-D crowd counting …