Crowd Counting
Leaderboards
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Greatest papers with code
C^3 Framework: An Open-source PyTorch Code for Crowd Counting
This technical report attempts to provide efficient and solid kits addressed on the field of crowd counting, which is denoted as Crowd Counting Code Framework (C$^3$F).
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank
Our results show that networks trained to regress to the ground truth targets for labeled data and to simultaneously learn to rank unlabeled data obtain significantly better, state-of-the-art results for both IQA and crowd counting.
ACTIVE LEARNING CROWD COUNTING IMAGE QUALITY ASSESSMENT LEARNING-TO-RANK REGRESSION
Switching Convolutional Neural Network for Crowd Counting
It is observed that the switch relays an image patch to a particular CNN column based on density of crowd.
CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting
• svishwa/crowdcount-cascaded-mtl
• 
Estimating crowd count in densely crowded scenes is an extremely challenging task due to non-uniform scale variations.
#2 best model for
Crowd Counting
on UCF CC 50
Crowd counting via scale-adaptive convolutional neural network
The task of crowd counting is to automatically estimate the pedestrian number in crowd images.
Leveraging Unlabeled Data for Crowd Counting by Learning to Rank
We propose a novel crowd counting approach that leverages abundantly available unlabeled crowd imagery in a learning-to-rank framework.
Locate, Size and Count: Accurately Resolving People in Dense Crowds via Detection
• val-iisc/lsc-cnn
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We introduce a detection framework for dense crowd counting and eliminate the need for the prevalent density regression paradigm.
SOTA for Crowd Counting on ShanghaiTech B
Stacked Pooling: Improving Crowd Counting by Boosting Scale Invariance
• siyuhuang/crowdcount-stackpool
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In this work, we explore the cross-scale similarity in crowd counting scenario, in which the regions of different scales often exhibit high visual similarity.
Multi-scale Convolutional Neural Networks for Crowd Counting
• Ling-Bao/mscnn
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Crowd counting on static images is a challenging problem due to scale variations.
PCC Net: Perspective Crowd Counting via Spatial Convolutional Network
• gjy3035/PCC-Net
•
Crowd counting from a single image is a challenging task due to high appearance similarity, perspective changes and severe congestion.