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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 51–75 of 371 papers

TitleStatusHype
Neuron Linear Transformation: Modeling the Domain Shift for Crowd CountingCode1
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion ModelsCode1
Panoptic Segmentation: A ReviewCode1
CCTrans: Simplifying and Improving Crowd Counting with TransformerCode1
Adaptive Mixture Regression Network with Local Counting Map for Crowd CountingCode1
CLIP-Count: Towards Text-Guided Zero-Shot Object CountingCode1
ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary TransformerCode1
Focal Inverse Distance Transform Maps for Crowd LocalizationCode1
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language ModelCode1
A Survey on Deep Learning-based Single Image Crowd Counting: Network Design, Loss Function and Supervisory SignalCode1
Rethinking Spatial Invariance of Convolutional Networks for Object CountingCode1
RGB-T Multi-Modal Crowd Counting Based on TransformerCode1
Ambient Sound Helps: Audiovisual Crowd Counting in Extreme ConditionsCode1
Completely Self-Supervised Crowd Counting via Distribution MatchingCode1
Counting People by Estimating People FlowsCode1
Congested Crowd Instance Localization with Dilated Convolutional Swin TransformerCode1
CrowdVLM-R1: Expanding R1 Ability to Vision Language Model for Crowd Counting using Fuzzy Group Relative Policy RewardCode1
DAOT: Domain-Agnostically Aligned Optimal Transport for Domain-Adaptive Crowd CountingCode1
Densely Connected Convolutional NetworksCode1
Dense Point Prediction: A Simple Baseline for Crowd Counting and LocalizationCode1
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd CountingCode1
Domain-General Crowd Counting in Unseen ScenariosCode1
Dropout Injection at Test Time for Post Hoc Uncertainty Quantification in Neural NetworksCode1
Counting from Sky: A Large-scale Dataset for Remote Sensing Object Counting and A Benchmark MethodCode1
Crowd Counting in the Frequency DomainCode1
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