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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 151–160 of 371 papers

TitleStatusHype
Cross-Scene Crowd Counting via Deep Convolutional Neural Networks—0
BBA-net: A bi-branch attention network for crowd counting—0
Application-Driven AI Paradigm for Person Counting in Various Scenarios—0
Crossing the Line: Crowd Counting by Integer Programming with Local Features—0
Bayesian Multi Scale Neural Network for Crowd Counting—0
Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation—0
Bayesian Model Adaptation for Crowd Counts—0
A Deeply-Recursive Convolutional Network for Crowd Counting—0
Fine-grained Domain Adaptive Crowd Counting via Point-derived Segmentation—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
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