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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
Embodied Crowd Counting—0
Enhancing people localisation in drone imagery for better crowd management by utilising every pixel in high-resolution images—0
ANTHROPOS-V: benchmarking the novel task of Crowd Volume EstimationCode0
Bound Tightening Network for Robust Crowd Counting—0
Boosting Adverse Weather Crowd Counting via Multi-queue Contrastive Learning—0
Multi-modal Crowd Counting via Modal EmulationCode0
DenseTrack: Drone-based Crowd Tracking via Density-aware Motion-appearance SynergyCode0
FGA: Fourier-Guided Attention Network for Crowd Count Estimation—0
CountFormer: Multi-View Crowd Counting TransformerCode0
POPCat: Propagation of particles for complex annotation tasks—0
Flexible Heteroscedastic Count Regression with Deep Double Poisson NetworksCode0
Crowd Counting and Individual Localization Using Pseudo Square Label—0
VMambaCC: A Visual State Space Model for Crowd Counting—0
Causal Influence in Federated Edge Inference—0
Möbius Transform for Mitigating Perspective Distortions in Representation Learning—0
A Density-Guided Temporal Attention Transformer for Indiscernible Object Counting in Underwater Video—0
Robust Zero-Shot Crowd Counting and Localization With Adaptive Resolution SAM—0
Semi-supervised Counting via Pixel-by-pixel Density Distribution ModellingCode0
Virtual Classification: Modulating Domain-Specific Knowledge for Multidomain Crowd CountingCode0
Diffusion-based Data Augmentation for Object Counting Problems—0
Curriculum for Crowd Counting -- Is it Worthy?—0
Multimodal Crowd Counting with Pix2Pix GANs—0
A Lightweight Feature Fusion Architecture For Resource-Constrained Crowd Counting—0
FGENet: Fine-Grained Extraction Network for Congested Crowd Counting—0
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion Models—0
Scale-Aware Crowd Count Network with Annotation Error Correction—0
A Unified Simulation Framework for Visual and Behavioral Fidelity in Crowd Analysis—0
Regressor-Segmenter Mutual Prompt Learning for Crowd Counting—0
Learning Discriminative Features for Crowd Counting—0
Counting Manatee Aggregations using Deep Neural Networks and Anisotropic Gaussian KernelCode0
Deep Imbalanced Regression via Hierarchical Classification Adjustment—0
Crowd Counting in Harsh Weather using Image Denoising with Pix2Pix GANs—0
SYRAC: Synthesize, Rank, and CountCode0
Calibrating Uncertainty for Semi-Supervised Crowd Counting—0
Improved Knowledge Distillation for Crowd Counting on IoT DeviceCode0
Counting Crowds in Bad Weather—0
Accurate Gigapixel Crowd Counting by Iterative Zooming and Refinement—0
Why Existing Multimodal Crowd Counting Datasets Can Lead to Unfulfilled Expectations in Real-World Applications—0
Crowd Counting with Sparse Annotation—0
Trap-Based Pest Counting: Multiscale and Deformable Attention CenterNet Integrating Internal LR and HR Joint Feature Learning—0
Application-Driven AI Paradigm for Person Counting in Various Scenarios—0
Crowd Counting with Online Knowledge Learning—0
LCDnet: A Lightweight Crowd Density Estimation Model for Real-time Video Surveillance—0
PromptMix: Text-to-image diffusion models enhance the performance of lightweight networks—0
Density-based clustering with fully-convolutional networks for crowd flow detection from dronesCode0
A Unified Object Counting Network with Object Occupation PriorCode0
HDNet: A Hierarchically Decoupled Network for Crowd Counting—0
Crowd Density Estimation using Imperfect Labels—0
Counting Like Human: Anthropoid Crowd Counting on Modeling the Similarity of Objects—0
DASECount: Domain-Agnostic Sample-Efficient Wireless Indoor Crowd Counting via Few-shot Learning—0
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