28 citations · 44 across the 10 of their papers we have counts for
8 papers · 1 filter
DriveVLA-M0: Failure-Aware Memory Augmentation for Autonomous Driving
Zebin Xing, Yupeng Zheng, Qiang Chen +10
Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for end-to-end autonomous driving by enabling unified reasoning across perception, language, and p…
Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving
Linbo Wang, Yupeng Zheng, Qiang Chen +14
We introduce Latent-WAM, an efficient end-to-end autonomous driving framework that achieves strong trajectory planning through spatially-aware and dynamics-informed latent world re…
TaPD: Temporal-adaptive Progressive Distillation for Observation-Adaptive Trajectory Forecasting in Autonomous Driving
Mingyu Fan, Yi Liu, Hao Zhou +3
Trajectory prediction is essential for autonomous driving, enabling vehicles to anticipate the motion of surrounding agents to support safe planning. However, most existing predict…
GraphAD: Interaction Scene Graph for End-to-end Autonomous Driving
Yunpeng Zhang, Deheng Qian, Ding Li +11
Modeling complicated interactions among the ego-vehicle, road agents, and map elements has been a crucial part for safety-critical autonomous driving. Previous works on end-to-end…
Robust Trajectory Forecasting for Multiple Intelligent Agents in Dynamic Scene
Yanliang Zhu, Dongchun Ren, Mingyu Fan +3
Trajectory forecasting, or trajectory prediction, of multiple interacting agents in dynamic scenes, is an important problem for many applications, such as robotic systems and auton…
CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception
Sibo Zhang, Yuexin Ma, Ruigang Yang
This paper reviews the CVPR 2019 challenge on Autonomous Driving. Baidu's Robotics and Autonomous Driving Lab (RAL) providing 150 minutes labeled Trajectory and 3D Perception datas…
VisionNet: A Drivable-space-based Interactive Motion Prediction Network for Autonomous Driving
Yanliang Zhu, Deheng Qian, Dongchun Ren +1
The comprehension of environmental traffic situation largely ensures the driving safety of autonomous vehicles. Recently, the mission has been investigated by plenty of researches,…
StarNet: Pedestrian Trajectory Prediction using Deep Neural Network in Star Topology
Yanliang Zhu, Deheng Qian, Dongchun Ren +1
Pedestrian trajectory prediction is crucial for many important applications. This problem is a great challenge because of complicated interactions among pedestrians. Previous metho…