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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 191–200 of 371 papers

TitleStatusHype
Semi-Supervised Crowd Counting from Unlabeled Data—0
Fine-grained Domain Adaptive Crowd Counting via Point-derived Segmentation—0
Reducing Spatial Labeling Redundancy for Semi-supervised Crowd Counting—0
Cascaded Residual Density Network for Crowd Counting—0
Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network—0
Crowd Counting via Perspective-Guided Fractional-Dilation ConvolutionCode0
Direct Measure Matching for Crowd Counting—0
Region-Aware Network: Model Human's Top-Down Visual Perception Mechanism for Crowd Counting—0
A Generalized Loss Function for Crowd Counting and Localization—0
Hybrid attention network based on progressive embedding scale-context for crowd counting—0
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