12 citations · 14 across the 6 of their papers we have counts for
6 papers
SafeDriveRAG: Towards Safe Autonomous Driving with Knowledge Graph-based Retrieval-Augmented Generation
Hao Ye, Mengshi Qi, Zhaohong Liu +2
In this work, we study how vision-language models (VLMs) can be utilized to enhance the safety for the autonomous driving system, including perception, situational understanding, a…
Improving Partially Observed Trajectories Forecasting by Target-driven Self-Distillation
Peng Shu, Pengfei Zhu, Mengshi Qi +1
Accurate prediction of future trajectories of traffic agents is essential for ensuring safe autonomous driving. However, partially observed trajectories can significantly degrade t…
Improving Batch Normalization with TTA for Robust Object Detection in Self-Driving
Dacheng Liao, Mengshi Qi, Liang Liu +1
In current open real-world autonomous driving scenarios, challenges such as sensor failure and extreme weather conditions hinder the generalization of most autonomous driving perce…
T2SG: Traffic Topology Scene Graph for Topology Reasoning in Autonomous Driving
Changsheng Lv, Mengshi Qi, Liang Liu +1
Understanding the traffic scenes and then generating high-definition (HD) maps present significant challenges in autonomous driving. In this paper, we defined a novel Traffic Topol…
An efficient deep learning hashing neural network for mobile visual search
Heng Qi, Wu Liu, Liang Liu
Mobile visual search applications are emerging that enable users to sense their surroundings with smart phones. However, because of the particular challenges of mobile visual searc…
Frugal Online Incentive Mechanisms for Crowdsourcing Tasks Truthfully
Dong Zhao, Huadong Ma, Liang Liu
Mobile Crowd Sensing (MCS) is a new paradigm which takes advantage of pervasive smartphones to efficiently collect data, enabling numerous novel applications. To achieve good servi…