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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 161–170 of 371 papers

TitleStatusHype
Attention Scaling for Crowd Counting—0
Crowd Transformer Network—0
Crowd Scene Analysis using Deep Learning Techniques—0
Attentional Neural Fields for Crowd Counting—0
A Lightweight Feature Fusion Architecture For Resource-Constrained Crowd Counting—0
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP—0
CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability—0
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion Models—0
Crowd Density Estimation using Novel Feature Descriptor—0
Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs—0
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