  Event camera-based driver monitoring is emerging as a pivotal area of
research, driven by its significant advantages such as rapid response, low
latency, power efficiency, enhanced privacy, and prevention of undersampling.
Effective detection of driver distraction is crucial in driver monitoring
systems to enhance road safety and reduce accident rates. The integration of an
optimized sensor such as Event Camera with an optimized network is essential
for maximizing these benefits. This paper introduces the innovative concept of
sensing without seeing to detect driver distraction, leveraging computationally
efficient spiking neural networks (SNN). To the best of our knowledge, this
study is the first to utilize event camera data with spiking neural networks
for driver distraction. The proposed Spiking-DD network not only achieve state
of the art performance but also exhibit fewer parameters and provides greater
accuracy than current event-based methodologies.
