Distracted driving action recognition from naturalistic driving is crucial for both driver and pedestrian's safe and reliable experience. However, traditional computer vision techniques sometimes require a lot of supervision in terms of a large amount of annotated training data to detect distracted driving activities. Recently, the vision-language models have offered large-scale visual-textual pretraining that can be adapted to unsupervised task-specific learning like distracted activity recogni…