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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 151–175 of 371 papers

TitleStatusHype
DroneNet: Crowd Density Estimation using Self-ONNs for Drones—0
Scale-Aware Crowd Counting Using a Joint Likelihood Density Map and Synthetic Fusion Pyramid Network—0
A Survey on Computer Vision based Human Analysis in the COVID-19 Era—0
Improving Local Features with Relevant Spatial Information by Vision Transformer for Crowd CountingCode0
Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection—0
Revisiting Crowd Counting: State-of-the-art, Trends, and Future Perspectives—0
A Spatio-Temporal Attentive Network for Video-Based Crowd Counting—0
Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training—0
MAFNet: A Multi-Attention Fusion Network for RGB-T Crowd Counting—0
Multi-scale Feature Aggregation for Crowd Counting—0
Discrete-Constrained Regression for Local Counting ModelsCode0
Analysis of the Effect of Low-Overhead Lossy Image Compression on the Performance of Visual Crowd Counting for Smart City ApplicationsCode0
The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network—0
Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation—0
An Improved Normed-Deformable Convolution for Crowd CountingCode0
Indirect-Instant Attention Optimization for Crowd Counting in Dense Scenes—0
Reducing Capacity Gap in Knowledge Distillation with Review Mechanism for Crowd CountingCode0
Self-supervised Domain Adaptation in Crowd Counting—0
Glance to Count: Learning to Rank with Anchors for Weakly-supervised Crowd Counting—0
Fine-Grained Counting with Crowd-Sourced Supervision—0
Forget Less, Count Better: A Domain-Incremental Self-Distillation Learning Benchmark for Lifelong Crowd Counting—0
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
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