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Crowd Counting

Crowd Counting is a task to count people in image. It is mainly used in real-life for automated public monitoring such as surveillance and traffic control. Different from object detection, Crowd Counting aims at recognizing arbitrarily sized targets in various situations including sparse and cluttering scenes at the same time.

Source: Deep Density-aware Count Regressor

Papers

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Showing 126–150 of 371 papers

TitleStatusHype
MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground ImageryCode0
Locate, Size and Count: Accurately Resolving People in Dense Crowds via DetectionCode0
A Real-Time Deep Network for Crowd CountingCode0
Leveraging Unlabeled Data for Crowd Counting by Learning to RankCode0
Improving Local Features with Relevant Spatial Information by Vision Transformer for Crowd CountingCode0
Improving Object Counting with Heatmap RegulationCode0
Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale UpsamplingCode0
Locality-constrained Spatial Transformer Network for Video Crowd CountingCode0
Counting Manatee Aggregations using Deep Neural Networks and Anisotropic Gaussian KernelCode0
Bayesian Loss for Crowd Count Estimation with Point SupervisionCode0
ANTHROPOS-V: benchmarking the novel task of Crowd Volume EstimationCode0
Image Crowd Counting Using Convolutional Neural Network and Markov Random FieldCode0
Discrete-Constrained Regression for Local Counting ModelsCode0
AutoScale: Learning to Scale for Crowd Counting and LocalizationCode0
ADCrowdNet: An Attention-injective Deformable Convolutional Network for Crowd UnderstandingCode0
An Improved Normed-Deformable Convolution for Crowd CountingCode0
Improved Knowledge Distillation for Crowd Counting on IoT DeviceCode0
CountFormer: Multi-View Crowd Counting TransformerCode0
Density-based clustering with fully-convolutional networks for crowd flow detection from dronesCode0
A Unified Object Counting Network with Object Occupation PriorCode0
DenseTrack: Drone-based Crowd Tracking via Density-aware Motion-appearance SynergyCode0
Dense Scale Network for Crowd CountingCode0
Context-Aware Crowd CountingCode0
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to RankCode0
Analysis of the Effect of Low-Overhead Lossy Image Compression on the Performance of Visual Crowd Counting for Smart City ApplicationsCode0
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