The task of crowd counting and localization is to predict the count and position of people in a
crowd, which is a practical and essential subtask in crowd analysis and smart city systems …

With the rapid advancement of deep learning, the performance of crowd counting has
improved significantly. Nonetheless, existing crowd counting models primarily depend on a …

With the rapid advancement of deep learning, the performance of crowd counting has
improved significantly. Nonetheless, existing crowd counting models primarily depend on a …

Crowd counting has substantial practical applications in various consumer-oriented areas,
particularly for safety assessments and marketing strategies. However, considering the …

Recent years have witnessed a remarkable proliferation of applications in smart cities.
Crowd analysis is a crucial subject, and it incorporates two subtasks in smart city systems, ie …

The integration of remote sensing object counting in the Mobile Edge Computing (MEC)
environment is of crucial significance and practical value. However, the presence of …

Dense crowd counting has become an essential technology for urban security management.
The traditional crowd counting methods mainly apply to the scene with a single view and …

Crowd counting, a crucial computer vision task, aims at estimating the number of individuals
in various environments. Each person in crowd counting datasets is typically annotated by a …

Currently, tracking by detection technique is widely used in crowd or vehicle counting.
However, it is difficult to meet detection and counting with mixed pedestrian and vehicular …

With the rapid development of society, crowded scenes can be seen almost everywhere.
Therefore, it is important to accurately predict the number and density distribution of people …