A review of synthetic image data and its use in computer vision
Development of computer vision algorithms using convolutional neural networks and deep
learning has necessitated ever greater amounts of annotated and labelled data to produce …
learning has necessitated ever greater amounts of annotated and labelled data to produce …
[HTML][HTML] Recent trends in crowd analysis: A review
When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …
parades or other sorts of people gatherings, they are confronted to multiple security issues …
Cnn-based density estimation and crowd counting: A survey
Accurately estimating the number of objects in a single image is a challenging yet
meaningful task and has been applied in many applications such as urban planning and …
meaningful task and has been applied in many applications such as urban planning and …
Taxonomy of anomaly detection techniques in crowd scenes
A Aldayri, W Albattah - Sensors, 2022 - mdpi.com
With the widespread use of closed-circuit television (CCTV) surveillance systems in public
areas, crowd anomaly detection has become an increasingly critical aspect of the intelligent …
areas, crowd anomaly detection has become an increasingly critical aspect of the intelligent …
CLRNet: A cross locality relation network for crowd counting in videos
In this article, we propose a new cross locality relation network (CLRNet) to generate high-
quality crowd density maps for crowd counting in videos. Specifically, a cross locality relation …
quality crowd density maps for crowd counting in videos. Specifically, a cross locality relation …
[HTML][HTML] Estimating optical flow: A comprehensive review of the state of the art
Optical flow estimation is a crucial task in computer vision that provides low-level motion
information. Despite recent advances, real-world applications still present significant …
information. Despite recent advances, real-world applications still present significant …
Counting people by estimating people flows
Modern methods for counting people in crowded scenes rely on deep networks to estimate
people densities in individual images. As such, only very few take advantage of temporal …
people densities in individual images. As such, only very few take advantage of temporal …
Crowd analysis in video surveillance: A review
Crowd behavior investigation in images/videos is an important task applied in areas such as
people counting, density estimation, emotion recognition, motion detection, and flow …
people counting, density estimation, emotion recognition, motion detection, and flow …
Joint cnn and transformer network via weakly supervised learning for efficient crowd counting
F Wang, K Liu, F Long, N Sang, X Xia… - arXiv preprint arXiv …, 2022 - arxiv.org
Currently, for crowd counting, the fully supervised methods via density map estimation are
the mainstream research directions. However, such methods need location-level annotation …
the mainstream research directions. However, such methods need location-level annotation …
Estimating people flows to better count them in crowded scenes
Modern methods for counting people in crowded scenes rely on deep networks to estimate
people densities in individual images. As such, only very few take advantage of temporal …
people densities in individual images. As such, only very few take advantage of temporal …