Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention

This is the official GitHub Repo for the paper Robust Multiview Multimodal Driver Monitoring System Using Masked Multi-Head Self-Attention accepted by the MULA workshop at CVPR 2023.

TODO:

• Upload our manually annotated labels.
• Upload the code of MHSA.
• Upload the code of SuMoCo.
• Upload the code for training and evaluation.

STEP1: Access the DAD dataset.

1. Visit the official DAD repo.
2. Find the link for data downloading.
3. Download the data.
4. Unzip the data into the folder data (create if not exists) under this repo.

STEP2: Prepare the dataset.

1. Copy and paste label.csv into the folder data.
2. Run python preprocess.py to generate the pickle files for the training set and the test set. You can specify the arguments to create your own dataset.

STEP3: Train the model.

• Run train.py to train the model. You can specify the arguments, e.g., which data sources or fusion methods to use...