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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 321–330 of 371 papers

TitleStatusHype
Fully Convolutional Crowd Counting On Highly Congested Scenes—0
Generalizing semi-supervised generative adversarial networks to regression using feature contrasting—0
Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs—0
Glance to Count: Learning to Rank with Anchors for Weakly-supervised Crowd Counting—0
HA-CCN: Hierarchical Attention-based Crowd Counting Network—0
HDNet: A Hierarchically Decoupled Network for Crowd Counting—0
Hybrid attention network based on progressive embedding scale-context for crowd counting—0
Hybrid Graph Neural Networks for Crowd Counting—0
Improving the Learning of Multi-column Convolutional Neural Network for Crowd Counting—0
Incorporating Side Information by Adaptive Convolution—0
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