Object detection using deep learning has attracted considerable interest from researchers
because of its competency in performing state-of-the-art tasks, including detection …

Recently, develo** automated video surveillance systems (VSSs) has become crucial to
ensure the security and safety of the population, especially during events involving large …

The current popular methods for video object segmentation (VOS) implement feature
matching through several hand-crafted modules that separately perform feature extraction …

Due to its promising results density map regression has been widely employed for image-
based crowd counting. The approach however often suffers from severe performance …

Abstract Domain shift across crowd data severely hinders crowd counting models to
generalize to unseen scenarios. Although domain adaptive crowd counting approaches …

Supervised crowd counting relies on manual labeling, which is costly and time-consuming.
This led to an increased interest in unsupervised methods. However, there is a significant …

Domain adaptation is commonly employed in crowd counting to bridge the domain gaps
between different datasets. However, existing domain adaptation methods tend to focus on …

Given an image, crowd counting aims to estimate the amount of target objects in the image.
With un-predictable installation situations of surveillance systems (or other equipments) …

Recently, crowd counting has attracted significant attention, particularly in the context of the
COVID-19 pandemic, due to its ability to automatically provide accurate crowd numbers in …

Crowd counting has important applications in public safety and pandemic control. A robust
and practical crowd counting system has to be capable of continuously learning with the …