Understanding deep learning techniques for image segmentation
The machine learning community has been overwhelmed by a plethora of deep learning--
based approaches. Many challenging computer vision tasks, such as detection, localization …
based approaches. Many challenging computer vision tasks, such as detection, localization …
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 generalized loss function for crowd counting and localization
Previous work shows that a better density map representation can improve the performance
of crowd counting. In this paper, we investigate learning the density map representation …
of crowd counting. In this paper, we investigate learning the density map representation …
Reppoints: Point set representation for object detection
Modern object detectors rely heavily on rectangular bounding boxes, such as anchors,
proposals and the final predictions, to represent objects at various recognition stages. The …
proposals and the final predictions, to represent objects at various recognition stages. The …
Scale aggregation network for accurate and efficient crowd counting
X Cao, Z Wang, Y Zhao, F Su - Proceedings of the …, 2018 - openaccess.thecvf.com
In this paper, we propose a novel encoder-decoder network, called extit {Scale Aggregation
Network (SANet)}, for accurate and efficient crowd counting. The encoder extracts multi …
Network (SANet)}, for accurate and efficient crowd counting. The encoder extracts multi …
Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques
The rampant coronavirus disease 2019 (COVID-19) has brought global crisis with its deadly
spread to more than 180 countries, and about 3,519,901 confirmed cases along with …
spread to more than 180 countries, and about 3,519,901 confirmed cases along with …
Occlusion-aware R-CNN: Detecting pedestrians in a crowd
Pedestrian detection in crowded scenes is a challenging problem since the pedestrians
often gather together and occlude each other. In this paper, we propose a new occlusion …
often gather together and occlude each other. In this paper, we propose a new occlusion …
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 …
Optimal transport minimization: Crowd localization on density maps for semi-supervised counting
The accuracy of crowd counting in images has improved greatly in recent years due to the
development of deep neural networks for predicting crowd density maps. However, most …
development of deep neural networks for predicting crowd density maps. However, most …
Towards perspective-free object counting with deep learning
D Onoro-Rubio, RJ López-Sastre - … The Netherlands, October 11–14, 2016 …, 2016 - Springer
In this paper we address the problem of counting objects instances in images. Our models
are able to precisely estimate the number of vehicles in a traffic congestion, or to count the …
are able to precisely estimate the number of vehicles in a traffic congestion, or to count the …