Fine-tuning visual models has been widely shown promising performance on many
downstream visual tasks. With the surprising development of pre-trained visual foundation …

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

Crowd counting is a fundamental yet challenging task, which desires rich information to
generate pixel-wise crowd density maps. However, most previous methods only used the …

Recent advances in visual-language models have shown remarkable zero-shot text-image
matching ability that is transferable to downstream tasks such as object detection and …

Counting dense crowds through computer vision technology has attracted widespread
attention. Most crowd counting datasets use point annotations. In this paper, we formulate …

Due to the widespread applications in real-world scenarios, metro ridership prediction is a
crucial but challenging task in intelligent transportation systems. However, conventional …

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 …

The success of modern farming and plant breeding relies on accurate and efficient collection
of data. For a commercial organization that manages large amounts of crops, collecting …

Crowd counting targets for determining the number of pedestrians in an image, which is of
crucial importance for smart city construction. The problem of scale variation is an ingrained …

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 …