Awesome Crowd Counting

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Awesome Crowd Counting

2018-04-23-Awesome Crowd Counting

纠错   23 Apr 2018

Awesome Crowd Counting

Papers

2018

  • Structured Inhomogeneous Density Map Learning for Crowd Counting (arXiv) [paper]
  • Body Structure Aware Deep Crowd Counting (TIP2018) [paper]
  • CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes (CVPR2018) [paper]
  • Leveraging Unlabeled Data for Crowd Counting by Learning to Rank (CVPR2018) [paper] [code]
  • Crowd Counting via Adversarial Cross-Scale Consistency Pursuit (CVPR2018)
  • DecideNet: Counting Varying Density Crowds Through Attention Guided Detection and Density (CVPR2018) [paper]
  • Crowd counting via scale-adaptive convolutional neural network (WACV2018) [paper] [code]

2017

  • Spatiotemporal Modeling for Crowd Counting in Videos (ICCV2017) [paper]
  • Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs (ICCV2017) [paper]
  • Spatiotemporal Modeling for Crowd Counting in Videos (ICCV2017) [paper]
  • CNN-based Cascaded Multi-task Learning of High-level Prior and Density Estimation for Crowd Counting (AVSS2017) [paper] [code]
  • Switching Convolutional Neural Network for Crowd Counting (CVPR2017) [paper] [code]
  • A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density Estimation (PR Letters) [paper]
  • Image Crowd Counting Using Convolutional Neural Network and Markov Random Field (arXiv) [paper] [code]
  • Multi-scale Convolution Neural Networks for Crowd Counting (arXiv) [paper] [code]

2016

  • Towards perspective-free object counting with deep learning (ECCV2016) [paper] [code]
  • Slicing Convolutional Neural Network for Crowd Video Understanding (CVPR2016) [paper] [code]
  • CrowdNet: A Deep Convolutional Network for Dense Crowd Counting (CVPR2016) [paper] [code]
  • Single-Image Crowd Counting via Multi-Column Convolutional Neural Network (CVPR2016) [paper] [code] [unofficial code]

2015

  • COUNT Forest: CO-voting Uncertain Number of Targets using Random Forest for Crowd Density Estimation (ICCV2015) [paper]
  • Cross-scene Crowd Counting via Deep Convolutional Neural Networks (CVPR2015) [paper] [code]

2013

  • Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images (CVPR2013) [paper]
  • Crossing the Line: Crowd Counting by Integer Programming with Local Features (CVPR2013) [paper]

2012

  • Feature mining for localised crowd counting (ECCV2012) [paper]

2008

  • Privacy preserving crowd monitoring: Counting people without people models or tracking (CVPR 2008) [paper]

Datasets

Performance

The project is being continually updated.

ShanghaiTech Part A

Method MAE MSE PSNR SSIM Model Size Params Runtime (ms) Pre-trained
DAN 81.8 134.7 - - - - - -
CSR 68.2 115.0 23.79 0.76 - - - -
MCNN 110.2 173.2 21.4 0.52 0.12M - - -

ShanghaiTech Part B

Method MAE MSE
DAN 13.2 20.1
BSAD 20.2 35.6
CSR 10.6 16.0
MCNN 26.4 41.3

UCF_CC_50

| Method | MAE | MSE | | — | — | — | | DAN | 309.6 | 402.64 | | BSAD | 409.5 | 563.7 | | CSR | 266.1 | 397.5 |

WorldExpo’10

| Method | S1 | S2 | S3 | S4 | S5 | Avg. | | — | — | — | — | — | — | — | | DAN | 4.1 | 11.1 | 10.7 | 16.2 | 5.0 | 9.4 | | BSAD | 4.1 | 21.7 | 11.9 | 11.0 | 3.5 | 10.5 | | CSR | 2.9 | 11.5 | 8.6 | 16.6 | 3.4 | 8.6 |

UCSD

| Method | MAE | MSE | | — | — | — | | BSAD | 1.00 | 1.40 |

Tools

  • Density Map Generation from Key Points [Code]

上篇： 2017-12-28-ENet

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