Research advances and challenges of autonomous and connected ground vehicles
Autonomous vehicle (AV) technology can provide a safe and convenient transportation
solution for the public, but the complex and various environments in the real world make it …
solution for the public, but the complex and various environments in the real world make it …
A survey of recent advances in cnn-based single image crowd counting and density estimation
VA Sindagi, VM Patel - Pattern Recognition Letters, 2018 - Elsevier
Estimating count and density maps from crowd images has a wide range of applications
such as video surveillance, traffic monitoring, public safety and urban planning. In addition …
such as video surveillance, traffic monitoring, public safety and urban planning. In addition …
Single-image crowd counting via multi-column convolutional neural network
This paper aims to develop a method that can accurately estimate the crowd count from an
individual image with arbitrary crowd density and arbitrary perspective. To this end, we have …
individual image with arbitrary crowd density and arbitrary perspective. To this end, we have …
Decidenet: Counting varying density crowds through attention guided detection and density estimation
In real-world crowd counting applications, the crowd densities vary greatly in spatial and
temporal domains. A detection based counting method will estimate crowds accurately in …
temporal domains. A detection based counting method will estimate crowds accurately in …
Locate, size, and count: accurately resolving people in dense crowds via detection
DB Sam, SV Peri, MN Sundararaman… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
We introduce a detection framework for dense crowd counting and eliminate the need for the
prevalent density regression paradigm. Typical counting models predict crowd density for an …
prevalent density regression paradigm. Typical counting models predict crowd density for an …
Localization in the crowd with topological constraints
We address the problem of crowd localization, ie, the prediction of dots corresponding to
people in a crowded scene. Due to various challenges, a localization method is prone to …
people in a crowded scene. Due to various challenges, a localization method is prone to …
Crowd counting with deep negative correlation learning
Deep convolutional networks (ConvNets) have achieved unprecedented performances on
many computer vision tasks. However, their adaptations to crowd counting on single images …
many computer vision tasks. However, their adaptations to crowd counting on single images …
Crowd counting via scale-adaptive convolutional neural network
L Zhang, M Shi, Q Chen - 2018 IEEE winter conference on …, 2018 - ieeexplore.ieee.org
The task of crowd counting is to automatically estimate the pedestrian number in crowd
images. To cope with the scale and perspective changes that commonly exist in crowd …
images. To cope with the scale and perspective changes that commonly exist in crowd …
Count forest: Co-voting uncertain number of targets using random forest for crowd density estimation
VQ Pham, T Kozakaya… - Proceedings of the …, 2015 - openaccess.thecvf.com
This paper presents a patch-based approach for crowd density estimation in public scenes.
We formulate the problem of estimating density in a structured learning framework applied to …
We formulate the problem of estimating density in a structured learning framework applied to …
Video object segmentation and tracking: A survey
Object segmentation and object tracking are fundamental research areas in the computer
vision community. These two topics are difficult to handle some common challenges, such …
vision community. These two topics are difficult to handle some common challenges, such …