BoostingVRME

🔧 Setup

STEP1: bash setup.sh

STEP2: conda activate BoostVRME

STEP3: pip install -r ./requirements.txt

💻 Example of Using Pre-trained Models

If you want to run the pre-trained model on SAMMLV, use python main.py --dataset_name SAMMLV --train False

Note: The preprocessed data and pre-trained models can be obtained through the link: https://drive.google.com/drive/folders/1eSZWKSagQDt2w9ua3fSPJGKA0POVqJo0?usp=sharing

💻 Examples of Neural Network Training

STEP 1: Download the $CAS(ME)^3$ raw data by asking the paper authors

STEP 2: Modify main.py; load_excel.py; load_images.py

STEP 3: Run python main.py --dataset_name CASME_3 --train True --flow_process True

🎓 Acknowledgement

We referred to MEAN_Spot-then-recognize, and would like to express our sincere thanks to the authors.

📜 Citation

If you find this repository helpful, please consider citing:

@inproceedings{10.1145/3746027.3762026,
  title={Boosting Micro-Expression Analysis via Prior-Guided Video-Level Regression},
  author={Guo, Zizheng and Zou, Bochao and Jia, Yinuo and Li, Xiangyu and Ma, Huimin},
  year={2025},
  isbn = {9798400720352},
  publisher = {Association for Computing Machinery},
  address = {New York, NY, USA},
  doi = {10.1145/3746027.3762026},
  booktitle={Proceedings of the 33rd ACM International Conference on Multimedia},
  location = {Dublin, Ireland},
  series = {MM '25}
}