TKDE 2021 Paper
DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction
Datasets
Yahoo! Bousai Crowd Data is now available at Yahoo! Japan Research website.
https://randd.yahoo.co.jp/en/softwaredata
- Please fill in Application PDF for Use of Yahoo! Bousai Crowd Data.
- Send it to yjresearch-data “at” mail.yahoo.co.jp.
- https://s.yimg.jp/dl/research_lab/randd/software_data/application_form_YJ21_10042184_en.pdf
- See the sample PDF ./YahooBousaiCrowdData/application_form_YJ21_10042184_en_sample.pdf.
- The fields below the underline on the application form do not need to be filled in.
- If there is any issue, please kindly ask Kota Tsubouchi ktsubouc@yahoo-corp.jp about the data access.
Model
Please check DeepCrowd.py or workBousaiTYO(OSA)_ours.
Dependencies
Working environment and major dependencies:
- Ubuntu 16.04.6 LTS
- Python 3 (>= 3.5; Anaconda Distribution)
- NumPy (>= 1.11.0)
- pandas (>= 0.18.0)
- TensorFlow/tensorflow-gpu (= 1.1x.0)
- Keras (>= 2.0.8)
Citation
If you find anything in this repository useful to your research, please cite our paper :) We sincerely appreciate it. DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction
@article{jiang2021deepcrowd,
title={DeepCrowd: A Deep Model for Large-Scale Citywide Crowd Density and Flow Prediction},
author={Jiang, Renhe and Cai, Zekun and Wang, Zhaonan and Yang, Chuang and Fan, Zipei and Chen, Quanjun and Tsubouchi, Kota and Song, Xuan and Shibasaki, Ryosuke},
journal={IEEE Transactions on Knowledge and Data Engineering},
year={2021},
publisher={IEEE}
}