/IVAC-P2L

IVAC-P2L: Leveraging Irregular Repetition Priors for Improving Video Action Counting

Primary LanguagePythonMIT LicenseMIT

Hang Wang1,2 | Zhi-Qi Cheng3 | Youtian Du1 | Lei Zhang2
1Xi'an Jiaotong University, 2The Hong Kong Polytechnic University, 3Carnegie Mellon University

Preparing Datasets

We train on the training set of the RepCount-A dataset, and test on the testing set of the RepCount-A dataset, the validation sets of the UCFRep and Countix datasets.

Download datasets: RepCount-A, UCFRep, Countix

Train

on the training set of the RepCount-A dataset

python train.py

Test

on the testing set of the RepCount-A dataset

python test.py

Pre-trained Checkpoint on RepCount-A

We also provide a pre-trained model for RepCount-A, which can be downloaded from this Google Drive link.

Acknowledgement

Thanks for works of TransRAC. Our code is based on these implementations.

Citation

@misc{wang2024ivacp2lleveragingirregularrepetition,
      title={IVAC-P2L: Leveraging Irregular Repetition Priors for Improving Video Action Counting}, 
      author={Hang Wang and Zhi-Qi Cheng and Youtian Du and Lei Zhang},
      year={2024},
      eprint={2403.11959},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2403.11959}, 
}

Contact

If you have any questions, please feel free to contact: cshwang@comp.polyu.edu.hk

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