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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 51–75 of 371 papers

TitleStatusHype
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
Semi-Supervised Crowd Counting with Contextual Modeling: Facilitating Holistic Understanding of Crowd ScenesCode1
Crowd Counting in Harsh Weather using Image Denoising with Pix2Pix GANs—0
SYRAC: Synthesize, Rank, and CountCode0
Boosting Detection in Crowd Analysis via Underutilized Output FeaturesCode1
Point-Query Quadtree for Crowd Counting, Localization, and MoreCode1
Calibrating Uncertainty for Semi-Supervised Crowd Counting—0
DAOT: Domain-Agnostically Aligned Optimal Transport for Domain-Adaptive Crowd CountingCode1
Improved Knowledge Distillation for Crowd Counting on IoT DeviceCode0
ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary TransformerCode1
Counting Crowds in Bad Weather—0
Accurate Gigapixel Crowd Counting by Iterative Zooming and Refinement—0
CLIP-Count: Towards Text-Guided Zero-Shot Object CountingCode1
Why Existing Multimodal Crowd Counting Datasets Can Lead to Unfulfilled Expectations in Real-World Applications—0
Crowd Counting with Sparse Annotation—0
CrowdCLIP: Unsupervised Crowd Counting via Vision-Language ModelCode1
Trap-Based Pest Counting: Multiscale and Deformable Attention CenterNet Integrating Internal LR and HR Joint Feature Learning—0
Explicit Attention-Enhanced Fusion for RGB-Thermal Perception TasksCode1
Application-Driven AI Paradigm for Person Counting in Various Scenarios—0
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion ModelsCode1
Crowd Counting with Online Knowledge Learning—0
Cross-head Supervision for Crowd Counting with Noisy AnnotationsCode1
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