Human Driving Focus
Human driving focus research investigates how attention is directed during driving tasks, aiming to improve driver assistance systems and autonomous vehicle safety. Current research emphasizes developing models that efficiently process visual information, often employing transformer architectures, convolutional neural networks, and recurrent neural networks to achieve accurate object detection, scene understanding, and action prediction. This work is significant for enhancing the reliability and safety of both human-driven and autonomous vehicles by improving perception and decision-making capabilities in complex driving scenarios.
Papers
Motor Focus: Fast Ego-Motion Prediction for Assistive Visual Navigation
Hao Wang, Jiayou Qin, Xiwen Chen, Ashish Bastola, John Suchanek, Zihao Gong, Abolfazl Razi
Efficiency in Focus: LayerNorm as a Catalyst for Fine-tuning Medical Visual Language Pre-trained Models
Jiawei Chen, Dingkang Yang, Yue Jiang, Mingcheng Li, Jinjie Wei, Xiaolu Hou, Lihua Zhang