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Domain-general Crowd Counting in Unseen Scenarios

Official PyTorch implementation of 'Domain-general Crowd Counting in Unseen Scenarios'.(AAAI 2023 Oral) [arXiv]

overview

Preparation

Python ≥ 3.7.

To install the required packages, please run:

pip install -r requirements.txt

For the data preparation, we follow the processing code in C-3-Framework. (Find processed UCF-QNRF here)

Train

Set up the settings in main.py
Run 'main.py'

Evaluation

Download our trained model, SHA or SHB.
Modify the path to the dataset and model for evaluation in 'test.py'.
Run 'test.py'

Acknowledgement

Part of codes are borrowed from DomainBed and dg_mmld. Thanks for their great work!

Citation

If you find this work useful, please cite

@article{du2022domain,
  title={Domain-general Crowd Counting in Unseen Scenarios},
  author={Du, Zhipeng and Deng, Jiankang and Shi, Miaojing},
  journal={arXiv preprint arXiv:2212.02573},
  year={2022}
}