5 papers
CogDriver: Integrating Cognitive Inertia for Temporally Coherent Planning in Autonomous Driving
Pei Liu, Qingtian Ning, Xinyan Lu +6
The pursuit of autonomous agents capable of temporally coherent planning is hindered by a fundamental flaw in current vision-language models (VLMs): they lack cognitive inertia. Op…
OmniScene: Attention-Augmented Multimodal 4D Scene Understanding for Autonomous Driving
Pei Liu, Hongliang Lu, Haichao Liu +5
Human vision is capable of transforming two-dimensional observations into an egocentric three-dimensional scene understanding, which underpins the ability to translate complex scen…
VLM-E2E: Enhancing End-to-End Autonomous Driving with Multimodal Driver Attention Fusion
Pei Liu, Haipeng Liu, Haichao Liu +3
Human drivers adeptly navigate complex scenarios by utilizing rich attentional semantics, but the current autonomous systems struggle to replicate this ability, as they often lose…
Scene-Aware Explainable Multimodal Trajectory Prediction
Pei Liu, Haipeng Liu, Xingyu Liu +4
Advancements in intelligent technologies have significantly improved navigation in complex traffic environments by enhancing environment perception and trajectory prediction for au…
HeightFormer: A Semantic Alignment Monocular 3D Object Detection Method from Roadside Perspective
Pei Liu, Zihao Zhang, Haipeng Liu +3
The on-board 3D object detection technology has received extensive attention as a critical technology for autonomous driving, while few studies have focused on applying roadside se…