6 papers
Cross-Paradigm Evaluation of Gaze-Based Semantic Object Identification for Intelligent Vehicles
Penghao Deng, Jidong J. Yang, Jiachen Bian
Understanding where drivers direct their visual attention during driving, as characterized by gaze behavior, is critical for developing next-generation advanced driver-assistance s…
VisitHGNN: Heterogeneous Graph Neural Networks for Modeling Point-of-Interest Visit Patterns
Lin Pang, Jidong J. Yang
Understanding how urban residents travel between neighborhoods and destinations is critical for transportation planning, mobility management, and public health. By mining historica…
Multi-Agent Visual-Language Reasoning for Comprehensive Highway Scene Understanding
Yunxiang Yang, Ningning Xu, Jidong J. Yang
This paper introduces a multi-agent framework for comprehensive highway scene understanding, designed around a mixture-of-experts strategy. In this framework, a large generic visio…
Structured Prompting and Multi-Agent Knowledge Distillation for Traffic Video Interpretation and Risk Inference
Yunxiang Yang, Ningning Xu, Jidong J. Yang
Comprehensive highway scene understanding and robust traffic risk inference are vital for advancing Intelligent Transportation Systems (ITS) and autonomous driving. Traditional app…
Enhancing autonomous vehicle safety in rain: a data-centric approach for clear vision
Mark A. Seferian, Jidong J. Yang
Autonomous vehicles face significant challenges in navigating adverse weather, particularly rain, due to the visual impairment of camera-based systems. In this study, we leveraged…
Leveraging Scene Geometry and Depth Information for Robust Image Deraining
Ningning Xu, Jidong J. Yang
Image deraining holds great potential for enhancing the vision of autonomous vehicles in rainy conditions, contributing to safer driving. Previous works have primarily focused on e…