3 papers
cs.CV2026
FlowAD: Ego-Scene Interactive Modeling for Autonomous Driving
Mingzhe Guo, Yixiang Yang, Chuanrong Han +4
Effective environment modeling is the foundation for autonomous driving, underpinning tasks from perception to planning. However, current paradigms often inadequately consider the…
cs.CV2024
Cyclic Refiner: Object-Aware Temporal Representation Learning for Multi-View 3D Detection and Tracking
Mingzhe Guo, Zhipeng Zhang, Liping Jing +3
We propose a unified object-aware temporal learning framework for multi-view 3D detection and tracking tasks. Having observed that the efficacy of the temporal fusion strategy in r…
cs.CV2024
End-to-End Autonomous Driving without Costly Modularization and 3D Manual Annotation
Mingzhe Guo, Zhipeng Zhang, Yuan He +2
We propose UAD, a method for vision-based end-to-end autonomous driving (E2EAD), achieving the best open-loop evaluation performance in nuScenes, meanwhile showing robust closed-lo…