This is the PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes in CVPR 2018, which delivered a state-of-the-art, straightforward and end-to-end architecture for crowd counting tasks.
CC visdrone Dataset: web_site
We strongly recommend Anaconda or Google Colab as the environment.
Python: 3.6
CUDA: 10.1
Follow the CSRNet_PyTorch.ipynb. You can try to modify the notebook and see the output of each image.
If you find the CSRNet useful, please cite the CSRNet our paper. Thank you!
@inproceedings{li2018csrnet,
title={CSRNet: Dilated convolutional neural networks for understanding the highly congested scenes},
author={Li, Yuhong and Zhang, Xiaofan and Chen, Deming},
booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
pages={1091--1100},
year={2018}
}