Counting high‐density objects quickly and accurately is a popular area of research. Crowd
counting has significant social and economic value and is a major focus in artificial …

Crowd detection and counting are important tasks in several applications of crowd analysis
including traffic management, public safety and event planning. Automatic crowd counting …

Vision crowd counting task has made remarkable process in recent years thanks to the
development of CNNs. However, this field has run into bottleneck since CNNs, by their …

Existing works mainly focus on crowd and ignore the confusion regions which contain
extremely similar appearance to crowd in the background, while crowd counting needs to …

Crowd counting has achieved significant progress by training regressors to predict instance
positions. In heavily crowded scenarios however regressors are challenged by …

This work considers supervised learning to count from images and their corresponding point
annotations. Where density-based counting methods typically use the point annotations only …

Single image crowd counting is a challenging computer vision problem with wide
applications in public safety, city planning, traffic management, etc. With the recent …

This paper proposes an adaptive auxiliary task learning-based approach for transport object
counting problems such as humans and vehicles. These problems are essential in many …

This paper proposes an adaptive auxiliary task learning based approach for object counting
problems. Unlike existing auxiliary task learning based methods, we develop an attention …

Crowd counting is essential for video surveillance and public safety. The performance of
counting models has been greatly improved with the rapid development of Convolution …