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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 281–290 of 371 papers

TitleStatusHype
L2HCount:Generalizing Crowd Counting from Low to High Crowd Density via Density Simulation—0
LCDnet: A Lightweight Crowd Density Estimation Model for Real-time Video Surveillance—0
Learning a perspective-embedded deconvolution network for crowd counting—0
Learning Discriminative Features for Crowd Counting—0
Learning Error-Driven Curriculum for Crowd Counting—0
Learning from Synthetic Data for Crowd Counting in the Wild—0
Learning Spatial Awareness to Improve Crowd Counting—0
Learning to Count in the Crowd from Limited Labeled Data—0
Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting—0
Leveraging Heterogeneous Auxiliary Tasks to Assist Crowd Counting—0
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