Crowd Counting
Leaderboards
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Greatest papers with code
NWPU-Crowd: A Large-Scale Benchmark for Crowd Counting
• gjy3035/Awesome-Crowd-Counting
• 
In the last decade, crowd counting attracts much attention of researchers due to its wide-spread applications, including crowd monitoring, public safety, space design, etc.
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
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.
#3 best model for
Crowd Counting
on UCF CC 50
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.
Crowd counting via scale-adaptive convolutional neural network
The task of crowd counting is to automatically estimate the pedestrian number in crowd images.
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.
#2 best model for
Crowd Counting
on ShanghaiTech A
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.
Bayesian Loss for Crowd Count Estimation with Point Supervision
ICCV 2019
• ZhihengCV/Baysian-Crowd-Counting
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In crowd counting datasets, each person is annotated by a point, which is usually the center of the head.
From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer
ICCV 2019
• xhp-hust-2018-2011/S-DCNet
•
A dense region can always be divided until sub-region counts are within the previously observed closed set.
SOTA for Crowd Counting on ShanghaiTech A