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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 181–190 of 371 papers

TitleStatusHype
Scene-Adaptive Attention Network for Crowd Counting—0
Scene Invariant Crowd Segmentation and Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)—0
Self-supervised Domain Adaptation in Crowd Counting—0
Semi-Supervised Crowd Counting via Self-Training on Surrogate Tasks—0
Shallow Feature Based Dense Attention Network for Crowd Counting—0
Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead—0
SOFA-Net: Second-Order and First-order Attention Network for Crowd Counting—0
Soft-Margin Mixture of Regressions—0
Spatiotemporal Modeling for Crowd Counting in Videos—0
SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing—0
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