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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 331–340 of 371 papers

TitleStatusHype
Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid—0
A Deeply-Recursive Convolutional Network for Crowd Counting—0
A-CCNN: adaptive ccnn for density estimation and crowd counting—0
Improving Object Counting with Heatmap RegulationCode0
Leveraging Unlabeled Data for Crowd Counting by Learning to RankCode0
Depth Information Guided Crowd Counting for Complex Crowd Scenes—0
CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested ScenesCode0
Structured Inhomogeneous Density Map Learning for Crowd Counting—0
DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density EstimationCode0
Incorporating Side Information by Adaptive Convolution—0
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