1 citations · 1 across the 3 of their papers we have counts for
4 papers
Multi-view Phase-aware Pedestrian-Vehicle Incident Reasoning Framework with Vision-Language Models
Hao Zhen, Yunxiang Yang, Jidong J. Yang
Pedestrian-vehicle incidents remain a critical urban safety challenge, with pedestrians accounting for over 20% of global traffic fatalities. Although existing video-based systems…
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 Nighttime Vehicle Detection with Day-to-Night Style Transfer and Labeling-Free Augmentation
Yunxiang Yang, Hao Zhen, Yongcan Huang +1
Existing deep learning-based object detection models perform well under daytime conditions but face significant challenges at night, primarily because they are predominantly traine…