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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 121–130 of 371 papers

TitleStatusHype
Cross-View Cross-Scene Multi-View Crowd Counting—0
Crowd counting with segmentation attention convolutional neural network—0
Crowd counting with crowd attention convolutional neural network—0
SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing—0
Counting in the 2020s: Binned Representations and Inclusive Performance Measures for Deep Crowd Counting Approaches—0
DR.VIC: Decomposition and Reasoning for Video Individual CountingCode1
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP—0
Joint CNN and Transformer Network via weakly supervised Learning for efficient crowd counting—0
CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability—0
Boosting Crowd Counting via Multifaceted AttentionCode1
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