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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 276–300 of 371 papers

TitleStatusHype
International Workshop on Continual Semi-Supervised Learning: Introduction, Benchmarks and Baselines—0
Inverse Attention Guided Deep Crowd Counting Network—0
Iterative Crowd Counting—0
JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method—0
Joint CNN and Transformer Network via weakly supervised Learning for efficient crowd counting—0
L2HCount:Generalizing Crowd Counting from Low to High Crowd Density via Density Simulation—0
LCDnet: A Lightweight Crowd Density Estimation Model for Real-time Video Surveillance—0
Learning a perspective-embedded deconvolution network for crowd counting—0
Learning Discriminative Features for Crowd Counting—0
Learning Error-Driven Curriculum for Crowd Counting—0
Learning from Synthetic Data for Crowd Counting in the Wild—0
Learning Spatial Awareness to Improve Crowd Counting—0
Learning to Count in the Crowd from Limited Labeled Data—0
Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting—0
Leveraging Heterogeneous Auxiliary Tasks to Assist Crowd Counting—0
MAFNet: A Multi-Attention Fusion Network for RGB-T Crowd Counting—0
Mask-aware networks for crowd counting—0
Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting—0
Möbius Transform for Mitigating Perspective Distortions in Representation Learning—0
Modeling Noisy Annotations for Crowd Counting—0
Motion-guided Non-local Spatial-Temporal Network for Video Crowd Counting—0
Multi-channel Deep Supervision for Crowd Counting—0
Multi-Level Attentive Convoluntional Neural Network for Crowd Counting—0
Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting—0
Multimodal Crowd Counting with Pix2Pix GANs—0
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