15 citations · 16 across the 5 of their papers we have counts for
5 papers · 1 filter
UV-M3TL: A Unified and Versatile Multimodal Multi-Task Learning Framework for Assistive Driving Perception
Wenzhuo Liu, Qiannan Guo, Zhen Wang +9
Advanced Driver Assistance Systems (ADAS) need to understand human driver behavior while perceiving their navigation context, but jointly learning these heterogeneous tasks would c…
SymDrive: Realistic and Controllable Driving Simulator via Symmetric Auto-regressive Online Restoration
Zhiyuan Liu, Daocheng Fu, Pinlong Cai +5
High-fidelity and controllable 3D simulation is essential for addressing the long-tail data scarcity in Autonomous Driving (AD), yet existing methods struggle to simultaneously ach…
MMTL-UniAD: A Unified Framework for Multimodal and Multi-Task Learning in Assistive Driving Perception
Wenzhuo Liu, Wenshuo Wang, Yicheng Qiao +9
Advanced driver assistance systems require a comprehensive understanding of the driver's mental/physical state and traffic context but existing works often neglect the potential be…
Stag-1: Towards Realistic 4D Driving Simulation with Video Generation Model
Lening Wang, Wenzhao Zheng, Dalong Du +8
4D driving simulation is essential for developing realistic autonomous driving simulators. Despite advancements in existing methods for generating driving scenes, significant chall…
OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving
Lening Wang, Wenzhao Zheng, Yilong Ren +4
Understanding the evolution of 3D scenes is important for effective autonomous driving. While conventional methods mode scene development with the motion of individual instances, w…