Driver Action Recognition

Driver action recognition (DAR) focuses on automatically identifying driver behaviors, primarily to improve road safety and enhance human-vehicle interaction. Current research emphasizes robust and efficient models, often employing transformer architectures, spiking neural networks, or vision-language models, to process data from multiple camera modalities (RGB, infrared, depth) and handle challenges like noisy labels, varying lighting conditions, and occlusions. These advancements are crucial for developing reliable driver monitoring systems in autonomous vehicles and advanced driver-assistance systems, contributing to accident prevention and improved road safety.