Deep learning in crowd counting: A survey
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 …
counting has significant social and economic value and is a major focus in artificial …
Steerer: Resolving scale variations for counting and localization via selective inheritance learning
Scale variation is a deep-rooted problem in object counting, which has not been effectively
addressed by existing scale-aware algorithms. An important factor is that they typically …
addressed by existing scale-aware algorithms. An important factor is that they typically …
Crowd counting in smart city via lightweight ghost attention pyramid network
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 …
crucial importance for smart city construction. The problem of scale variation is an ingrained …
Self-supervised learning with data-efficient supervised fine-tuning for crowd counting
Due to the expensive and laborious annotations of labeled data required by fully-supervised
learning in the crowd counting task, it is desirable to explore a method to reduce the labeling …
learning in the crowd counting task, it is desirable to explore a method to reduce the labeling …
Crossnet: Boosting crowd counting with localization
Generating high-quality density maps is a crucial step in crowd counting. It is obvious that
exploiting the head location of the people can naturally highlight the crowded area and …
exploiting the head location of the people can naturally highlight the crowded area and …
Lw-count: An effective lightweight encoding-decoding crowd counting network
Y Liu, G Cao, H Shi, Y Hu - … on Circuits and Systems for Video …, 2022 - ieeexplore.ieee.org
Crowd counting is a task of intelligent applications, and its operation efficiency is very
important. However, in order to obtain a better counting performance, most of the existing …
important. However, in order to obtain a better counting performance, most of the existing …
An Effective Lightweight Crowd Counting Method Based on an Encoder-Decoder Network for the Internet of Video Things
J Yi, F Chen, Z Shen, Y **ang, S **ao… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
An emerging Internet of Video Things (IoVT) application, crowd counting is a computer
vision task where the number of heads in a crowded scene is estimated. In recent years, it …
vision task where the number of heads in a crowded scene is estimated. In recent years, it …
RGB-T multi-modal crowd counting based on transformer
Crowd counting aims to estimate the number of persons in a scene. Most state-of-the-art
crowd counting methods based on color images can't work well in poor illumination …
crowd counting methods based on color images can't work well in poor illumination …
Spatial exchanging fusion network for RGB-T crowd counting
Abstract RGB-T crowd counting (RGB-T CC) aims to estimate the crowd population size
utilizing the complementary information from visible and thermal images. Current deep …
utilizing the complementary information from visible and thermal images. Current deep …
CCANet: A collaborative cross-modal attention network for RGB-D crowd counting
Y Liu, G Cao, B Shi, Y Hu - IEEE Transactions on Multimedia, 2023 - ieeexplore.ieee.org
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 …
count by combining training RGB images and depth images. However, these methods are …