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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

Showing 5160 of 371 papers

TitleStatusHype
Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd CountingCode1
Congested Crowd Instance Localization with Dilated Convolutional Swin TransformerCode1
Spatial Uncertainty-Aware Semi-Supervised Crowd CountingCode1
Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd CountingCode1
Rethinking Counting and Localization in Crowds:A Purely Point-Based FrameworkCode1
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge ResultsCode1
Detection, Tracking, and Counting Meets Drones in Crowds: A BenchmarkCode1
Deep learning with self-supervision and uncertainty regularization to count fish in underwater imagesCode1
Dense Point Prediction: A Simple Baseline for Crowd Counting and LocalizationCode1
TransCrowd: weakly-supervised crowd counting with transformersCode1
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