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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 101–150 of 371 papers

TitleStatusHype
Fine-Grained Crowd Counting—0
Fine-grained Domain Adaptive Crowd Counting via Point-derived Segmentation—0
Fully Convolutional Crowd Counting On Highly Congested Scenes—0
Crowd Counting with Density Adaption Networks—0
Crowd Counting with Deep Structured Scale Integration Network—0
CCCNet: An Attention Based Deep Learning Framework for Categorized Crowd Counting—0
A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View—0
FGA: Fourier-Guided Attention Network for Crowd Count Estimation—0
Crowd Counting with Decomposed Uncertainty—0
Crowd Counting with Online Knowledge Learning—0
Crowd counting with crowd attention convolutional neural network—0
Crowd counting with segmentation attention convolutional neural network—0
Causal Influence in Federated Edge Inference—0
Crowd Density Estimation using Imperfect Labels—0
Crowd Counting via Weighted VLAD on Dense Attribute Feature Maps—0
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion Models—0
CrowdFormer: Weakly-supervised Crowd counting with Improved Generalizability—0
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP—0
Cascaded Residual Density Network for Crowd Counting—0
A Study of Human Gaze Behavior During Visual Crowd Counting—0
Adaptive Density Map Generation for Crowd Counting—0
FGENet: Fine-Grained Extraction Network for Congested Crowd Counting—0
A Strong Baseline for Crowd Counting and Unsupervised People Localization—0
Cumulative Attribute Space for Age and Crowd Density Estimation—0
Curriculum for Crowd Counting -- Is it Worthy?—0
DAFE-FD: Density Aware Feature Enrichment for Face Detection—0
Crowd Counting via Hierarchical Scale Recalibration Network—0
Exploiting Sample Correlation for Crowd Counting With Multi-Expert Network—0
Calibrating Uncertainty for Semi-Supervised Crowd Counting—0
Crowd Counting Using Scale-Aware Attention Networks—0
Accurate Gigapixel Crowd Counting by Iterative Zooming and Refinement—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
Crowd Counting using Deep Recurrent Spatial-Aware Network—0
Crowd Counting Through Walls Using WiFi—0
A Spatio-Temporal Attentive Network for Video-Based Crowd Counting—0
Bound Tightening Network for Robust Crowd Counting—0
Crowd Counting on Heavily Compressed Images with Curriculum Pre-Training—0
Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining—0
Fine-Grained Counting with Crowd-Sourced Supervision—0
Crowd Counting in Harsh Weather using Image Denoising with Pix2Pix GANs—0
Crowd Counting Considering Network Flow Constraints in Videos—0
Crowd Counting by Self-supervised Transfer Colorization Learning and Global Prior Classification—0
Rethinking Global Context in Crowd Counting—0
A Short Overview of Multi-Modal Wi-Fi Sensing—0
Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid—0
Crowd Counting by Adapting Convolutional Neural Networks with Side Information—0
Crowd Counting and Individual Localization Using Pseudo Square Label—0
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks—0
Boosting Adverse Weather Crowd Counting via Multi-queue Contrastive Learning—0
A Density-Guided Temporal Attention Transformer for Indiscernible Object Counting in Underwater Video—0
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