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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 101–125 of 371 papers

TitleStatusHype
Multi-Stream Networks and Ground-Truth Generation for Crowd CountingCode0
MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground ImageryCode0
Crowd counting via scale-adaptive convolutional neural networkCode0
Locate, Size and Count: Accurately Resolving People in Dense Crowds via DetectionCode0
Multi-modal Crowd Counting via Modal EmulationCode0
Crowd Counting via Perspective-Guided Fractional-Dilation ConvolutionCode0
Crowd Counting With Deep Negative Correlation LearningCode0
A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density EstimationCode0
Car Object Counting and Position Estimation via Extension of the CLIP-EBC FrameworkCode0
Crowd Counting via Adversarial Cross-Scale Consistency PursuitCode0
Leveraging Unlabeled Data for Crowd Counting by Learning to RankCode0
Improving Local Features with Relevant Spatial Information by Vision Transformer for Crowd CountingCode0
C^3 Framework: An Open-source PyTorch Code for Crowd CountingCode0
Improving Object Counting with Heatmap RegulationCode0
Crowd Counting on Images with Scale Variation and Isolated ClustersCode0
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
Point-to-Region Loss for Semi-Supervised Point-Based Crowd CountingCode0
Flexible Heteroscedastic Count Regression with Deep Double Poisson NetworksCode0
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to RankCode0
Dual Path Multi-Scale Fusion Networks with Attention for Crowd CountingCode0
A Real-Time Deep Network for Crowd CountingCode0
Image Crowd Counting Using Convolutional Neural Network and Markov Random FieldCode0
Residual Regression With Semantic Prior for Crowd CountingCode0
Counting Manatee Aggregations using Deep Neural Networks and Anisotropic Gaussian KernelCode0
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