This repository is an implementation of crowd counting described in the paper "Image Crowd Counting Using Convolutional Neural Network and Markov Random Field". The fully connected regress network is implemented by Keras (Tensorflow backend). Others are implemented by Matlab.
If you find this code useful in your research, please cite:
@article{han2017image,
title={Image Crowd Counting Using Convolutional Neural Network and Markov Random Field},
author={Han, Kang and Wan, Wanggen and Yao, Haiyan and Hou, Li},
journal={arXiv preprint arXiv:1706.03686},
year={2017}
}
You can direct evalute the model's performance by running EvaluteUCF.m or EvaluateSHT.m using predicted patches' count. This process will apply Markov Random Field and get the global count.
If you want to train a new regress model, follow these steps:
UCF
MAE | MSE |
254.1 | 352.5 |
Shanghaitech
Part_A | Part_B | ||
MAE | MSE | MAE | MSE |
79.1 | 130.1 | 17.8 | 26.0 |