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Crowd Counting
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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.
논문
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EBC-ZIP: Improving Blockwise Crowd Counting with Zero-Inflated Poisson Regression
Point-to-Region Loss for Semi-Supervised Point-Based Crowd Counting
Crowd Scene Analysis using Deep Learning Techniques
Transformer-Based Dual-Optical Attention Fusion Crowd Head Point Counting and Localization Network
A Short Overview of Multi-Modal Wi-Fi Sensing
Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining
ProgRoCC: A Progressive Approach to Rough Crowd Counting
CrowdVLM-R1: Expanding R1 Ability to Vision Language Model for Crowd Counting using Fuzzy Group Relative Policy Reward
Taste More, Taste Better: Diverse Data and Strong Model Boost Semi-Supervised Crowd Counting
L2HCount:Generalizing Crowd Counting from Low to High Crowd Density via Density Simulation
Consistent-Point: Consistent Pseudo-Points for Semi-Supervised Crowd Counting and Localization
EHNet: An Efficient Hybrid Network for Crowd Counting and Localization
Video Individual Counting for Moving Drones
Embodied Crowd Counting
Enhancing people localisation in drone imagery for better crowd management by utilising every pixel in high-resolution images
ANTHROPOS-V: benchmarking the novel task of Crowd Volume Estimation
Bound Tightening Network for Robust Crowd Counting
Boosting Adverse Weather Crowd Counting via Multi-queue Contrastive Learning
Multi-modal Crowd Counting via Modal Emulation
DenseTrack: Drone-based Crowd Tracking via Density-aware Motion-appearance Synergy
Multi-modal Crowd Counting via a Broker Modality
FGA: Fourier-Guided Attention Network for Crowd Count Estimation
CountFormer: Multi-View Crowd Counting Transformer
POPCat: Propagation of particles for complex annotation tasks
Flexible Heteroscedastic Count Regression with Deep Double Poisson Networks
Improving Point-based Crowd Counting and Localization Based on Auxiliary Point Guidance
Crowd Counting and Individual Localization Using Pseudo Square Label
VMambaCC: A Visual State Space Model for Crowd Counting
Causal Influence in Federated Edge Inference
The Effectiveness of a Simplified Model Structure for Crowd Counting
Single Domain Generalization for Crowd Counting
CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification
Möbius Transform for Mitigating Perspective Distortions in Representation Learning
A Density-Guided Temporal Attention Transformer for Indiscernible Object Counting in Underwater Video
Robust Zero-Shot Crowd Counting and Localization With Adaptive Resolution SAM
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