We develop a supervised contrastive learning framework to recognize the distracted driving, in which the driver distraction behaviors can be quantified using their distances from normal ones in the latent space. Note that the dataset can be downloaded from the SAM-DD website.
- Visual examples
normal driving making hair
phoning texting
