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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 81–90 of 371 papers

TitleStatusHype
Densely Connected Convolutional NetworksCode1
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd CountingCode1
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion ModelsCode1
RGB-T Multi-Modal Crowd Counting Based on TransformerCode1
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language ModelCode1
Bi-level Alignment for Cross-Domain Crowd CountingCode1
A Self-Training Approach for Point-Supervised Object Detection and Counting in CrowdsCode1
Distribution Matching for Crowd CountingCode1
CODA: Counting Objects via Scale-aware Adversarial Density AdaptionCode0
Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale UpsamplingCode0
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