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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 51–100 of 371 papers

TitleStatusHype
Progressive Multi-resolution Loss for Crowd CountingCode1
Wide-Area Crowd Counting: Multi-View Fusion Networks for Counting in Large ScenesCode1
Optimal Transport Minimization: Crowd Localization on Density Maps for Semi-Supervised CountingCode1
PSGCNet: A Pyramidal Scale and Global Context Guided Network for Dense Object Counting in Remote Sensing ImagesCode1
Adaptive Mixture Regression Network with Local Counting Map for Crowd CountingCode1
CLIP-Count: Towards Text-Guided Zero-Shot Object CountingCode1
Free Lunch Enhancements for Multi-modal Crowd CountingCode1
Leveraging Self-Supervision for Cross-Domain Crowd CountingCode1
Ambient Sound Helps: Audiovisual Crowd Counting in Extreme ConditionsCode1
Completely Self-Supervised Crowd Counting via Distribution MatchingCode1
Localization in the Crowd with Topological ConstraintsCode1
Boosting Detection in Crowd Analysis via Underutilized Output FeaturesCode1
Densely Connected Convolutional NetworksCode1
Multiscale Crowd Counting and Localization By Multitask Point SupervisionCode1
ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary TransformerCode1
Congested Crowd Instance Localization with Dilated Convolutional Swin TransformerCode1
Neuron Linear Transformation: Modeling the Domain Shift for Crowd CountingCode1
Exploit the potential of Multi-column architecture for Crowd CountingCode1
Panoptic Segmentation: A ReviewCode1
Point-Query Quadtree for Crowd Counting, Localization, and MoreCode1
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
Focal Inverse Distance Transform Maps for Crowd LocalizationCode1
Counting from Sky: A Large-scale Dataset for Remote Sensing Object Counting and A Benchmark MethodCode1
Backdoor Attacks on Crowd CountingCode1
Rethinking Counting and Localization in Crowds: A Purely Point-Based FrameworkCode1
RGB-T Multi-Modal Crowd Counting Based on TransformerCode1
Counting People by Estimating People FlowsCode1
Semi-Supervised Crowd Counting with Contextual Modeling: Facilitating Holistic Understanding of Crowd ScenesCode1
Cross-head Supervision for Crowd Counting with Noisy AnnotationsCode1
Uniformity in Heterogeneity: Diving Deep Into Count Interval Partition for Crowd CountingCode1
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd CountingCode1
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion ModelsCode1
Detection, Tracking, and Counting Meets Drones in Crowds: A BenchmarkCode1
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
Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention NetworkCode1
CODA: Counting Objects via Scale-aware Adversarial Density AdaptionCode0
Locate, Size and Count: Accurately Resolving People in Dense Crowds via DetectionCode0
Locality-constrained Spatial Transformer Network for Video Crowd CountingCode0
CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd CountingCode0
Class-Agnostic CountingCode0
Leveraging Unlabeled Data for Crowd Counting by Learning to RankCode0
MRCNet: Crowd Counting and Density Map Estimation in Aerial and Ground ImageryCode0
A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density EstimationCode0
Improving Local Features with Relevant Spatial Information by Vision Transformer for Crowd CountingCode0
Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale UpsamplingCode0
Improving Object Counting with Heatmap RegulationCode0
Car Object Counting and Position Estimation via Extension of the CLIP-EBC FrameworkCode0
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