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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 251–260 of 371 papers

TitleStatusHype
PDANet: Pyramid Density-aware Attention Net for Accurate Crowd Counting—0
Plug-and-Play Rescaling Based Crowd Counting in Static Images—0
AutoScale: Learning to Scale for Crowd Counting and LocalizationCode0
Towards Building a Real Time Mobile Device Bird Counting System Through Synthetic Data Training and Model Compression—0
CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
Domain-adaptive Crowd Counting via High-quality Image Translation and Density Reconstruction—0
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting—0
Crowd Counting via Segmentation Guided Attention Networks and Curriculum LossCode0
Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method—0
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