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20232026
most citedGPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events

7 citations · 12 across the 10 of their papers we have counts for

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10 papers · 1 filter

cs.CV2026

SGTA: Scene-Graph Based Multi-Modal Traffic Agent for Video Understanding

Xingcheng Zhou, Mingyu Liu, Walter Zimmer +2

We present Scene-Graph Based Multi-Modal Traffic Agent (SGTA), a modular framework for traffic video understanding that combines structured scene graphs with multi-modal reasoning.…

cs.CV2026

Safety-Aligned 3D Object Detection: Single-Vehicle, Cooperative, and End-to-End Perspectives

Brian Hsuan-Cheng Liao, Chih-Hong Cheng, Hasan Esen +1

Perception plays a central role in connected and autonomous vehicles (CAVs), underpinning not only conventional modular driving stacks, but also cooperative perception systems and…

cs.CV2025

Generative AI for Autonomous Driving: Frontiers and Opportunities

Yuping Wang, Shuo Xing, Cui Can +46

Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation,…

cs.CV2025

LiDAR-Guided Monocular 3D Object Detection for Long-Range Railway Monitoring

Raul David Dominguez Sanchez, Xavier Diaz Ortiz, Xingcheng Zhou +4

Railway systems, particularly in Germany, require high levels of automation to address legacy infrastructure challenges and increase train traffic safely. A key component of automa…

cs.CV2025★ 1 cited

OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model

Xingcheng Zhou, Xuyuan Han, Feng Yang +3

We present OpenDriveVLA, a Vision Language Action model designed for end-to-end autonomous driving, built upon open-source large language models. OpenDriveVLA generates spatially g…

cs.CV2024

WARM-3D: A Weakly-Supervised Sim2Real Domain Adaptation Framework for Roadside Monocular 3D Object Detection

Xingcheng Zhou, Deyu Fu, Walter Zimmer +4

Existing roadside perception systems are limited by the absence of publicly available, large-scale, high-quality 3D datasets. Exploring the use of cost-effective, extensive synthet…

cs.CV2024

GraphRelate3D: Context-Dependent 3D Object Detection with Inter-Object Relationship Graphs

Mingyu Liu, Ekim Yurtsever, Marc Brede +6

Accurate and effective 3D object detection is critical for ensuring the driving safety of autonomous vehicles. Recently, state-of-the-art two-stage 3D object detectors have exhibit…

cs.CV2024★ 7 cited

GPT-4V as Traffic Assistant: An In-depth Look at Vision Language Model on Complex Traffic Events

Xingcheng Zhou, Alois C. Knoll

The recognition and understanding of traffic incidents, particularly traffic accidents, is a topic of paramount importance in the realm of intelligent transportation systems and in…

cs.CV2024★ 4 cited

A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlook

Mingyu Liu, Ekim Yurtsever, Jonathan Fossaert +5

Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for…

cs.CV2023

3D Understanding of Deformable Linear Objects: Datasets and Transferability Benchmark

Bare Luka Žagar, Tim Hertel, Mingyu Liu +2

Deformable linear objects are vastly represented in our everyday lives. It is often challenging even for humans to visually understand them, as the same object can be entangled so…