2 citations · 2 across the 3 of their papers we have counts for
4 papers
Explicit Geometric Chain-of-Thought for Vision-Language-Action in Autonomous Driving
Xingtai Gui, Yucheng Zhou, Dongqian Guo +3
Vision-language-action~(VLA) models have emerged as a promising paradigm for autonomous driving. However, existing VLA models still suffer from a fundamental mismatch: driving acti…
Bridging Scene Generation and Planning: Driving with World Model via Unifying Vision and Motion Representation
Xingtai Gui, Meijie Zhang, Tianyi Yan +5
End-to-end autonomous driving aims to generate safe and plausible planning policies from raw sensor input. Driving world models have shown great potential in learning rich represen…
TrajDiff: End-to-end Autonomous Driving without Perception Annotation
Xingtai Gui, Jianbo Zhao, Wencheng Han +5
End-to-end autonomous driving systems directly generate driving policies from raw sensor inputs. While these systems can extract effective environmental features for planning, rely…
SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving
Diankun Zhang, Guoan Wang, Runwen Zhu +15
End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system. Despite simplicity and clarity, the performance of end-to-end autonomous driv…