24 citations · 29 across the 7 of their papers we have counts for
3 papers · 1 filter
VRU-Accident: A Vision-Language Benchmark for Video Question Answering and Dense Captioning for Accident Scene Understanding
Younggun Kim, Ahmed S. Abdelrahman, Mohamed Abdel-Aty
Ensuring the safety of vulnerable road users (VRUs), such as pedestrians and cyclists, is a critical challenge for autonomous driving systems, as crashes involving VRUs often resul…
Video-to-Text Pedestrian Monitoring (VTPM): Leveraging Computer Vision and Large Language Models for Privacy-Preserve Pedestrian Activity Monitoring at Intersections
Ahmed S. Abdelrahman, Mohamed Abdel-Aty, Dongdong Wang
Computer vision has advanced research methodologies, enhancing system services across various fields. It is a core component in traffic monitoring systems for improving road safety…
Enhancing Traffic Safety with Parallel Dense Video Captioning for End-to-End Event Analysis
Maged Shoman, Dongdong Wang, Armstrong Aboah +1
This paper introduces our solution for Track 2 in AI City Challenge 2024. The task aims to solve traffic safety description and analysis with the dataset of Woven Traffic Safety (W…