23 citations · 29 across the 9 of their papers we have counts for
9 papers
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…
MagicRoad: Semantic-Aware 3D Road Surface Reconstruction via Obstacle Inpainting
Xingyue Peng, Yuandong Lyu, Lang Zhang +8
Road surface reconstruction is essential for autonomous driving, supporting centimeter-accurate lane perception and high-definition mapping in complex urban environments.While rece…
Learning Personalized Driving Styles via Reinforcement Learning from Human Feedback
Derun Li, Changye Li, Yue Wang +9
Generating human-like and adaptive trajectories is essential for autonomous driving in dynamic environments. While generative models have shown promise in synthesizing feasible tra…
Other Vehicle Trajectories Are Also Needed: A Driving World Model Unifies Ego-Other Vehicle Trajectories in Video Latent Space
Jian Zhu, Zhengyu Jia, Tian Gao +6
Advanced end-to-end autonomous driving systems predict other vehicles' motions and plan ego vehicle's trajectory. The world model that can foresee the outcome of the trajectory has…
UniPLV: Towards Label-Efficient Open-World 3D Scene Understanding by Regional Visual Language Supervision
Yuru Wang, Pei Liu, Songtao Wang +7
Open-world 3D scene understanding is a critical challenge that involves recognizing and distinguishing diverse objects and categories from 3D data, such as point clouds, without re…
Generalizing Motion Planners with Mixture of Experts for Autonomous Driving
Qiao Sun, Huimin Wang, Jiahao Zhan +7
Large real-world driving datasets have sparked significant research into various aspects of data-driven motion planners for autonomous driving. These include data augmentation, mod…
TOD3Cap: Towards 3D Dense Captioning in Outdoor Scenes
Bu Jin, Yupeng Zheng, Pengfei Li +12
3D dense captioning stands as a cornerstone in achieving a comprehensive understanding of 3D scenes through natural language. It has recently witnessed remarkable achievements, par…
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models
Xiaoyu Tian, Junru Gu, Bailin Li +7
A primary hurdle of autonomous driving in urban environments is understanding complex and long-tail scenarios, such as challenging road conditions and delicate human behaviors. We…
BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving
Tao Tang, Dafeng Wei, Zhengyu Jia +12
The rapid development of the autonomous driving industry has led to a significant accumulation of autonomous driving data. Consequently, there comes a growing demand for retrieving…