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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 101–125 of 371 papers

TitleStatusHype
Semi-supervised Crowd Counting via Density AgencyCode1
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
Redesigning Multi-Scale Neural Network for Crowd CountingCode1
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
Backdoor Attacks on Crowd CountingCode1
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
Rethinking Spatial Invariance of Convolutional Networks for Object CountingCode1
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
Bi-level Alignment for Cross-Domain Crowd CountingCode1
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
Counting in the 2020s: Binned Representations and Inclusive Performance Measures for Deep Crowd Counting Approaches—0
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