1 citations · 1 across the 4 of their papers we have counts for
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LiSTAR: Ray-Centric World Models for 4D LiDAR Sequences in Autonomous Driving
Pei Liu, Songtao Wang, Lang Zhang +9
Synthesizing high-fidelity and controllable 4D LiDAR data is crucial for creating scalable simulation environments for autonomous driving. This task is inherently challenging due t…
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…
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…
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…