most citedTraj-LLM: A New Exploration for Empowering Trajectory Prediction with Pre-trained Large Language Models

1 citations · 2 across the 9 of their papers we have counts for

collaborators

11 papers

cs.CV2025

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…

cs.CV2025

AMap: Distilling Future Priors for Ahead-Aware Online HD Map Construction

Ruikai Li, Xinrun Li, Mengwei Xie +12

Online High-Definition (HD) map construction is pivotal for autonomous driving. While recent approaches leverage historical temporal fusion to improve performance, we identify a cr…

cs.CV2025

Stability Under Scrutiny: Benchmarking Representation Paradigms for Online HD Mapping

Hao Shan, Ruikai Li, Han Jiang +8

As one of the fundamental modules in autonomous driving, online high-definition (HD) maps have attracted significant attention due to their cost-effectiveness and real-time capabil…

cs.CV2025

MapKD: Unlocking Prior Knowledge with Cross-Modal Distillation for Efficient Online HD Map Construction

Ziyang Yan, Ruikai Li, Zhiyong Cui +7

Online HD map construction is a fundamental task in autonomous driving systems, aiming to acquire semantic information of map elements around the ego vehicle based on real-time sen…

cs.RO2025

SAH-Drive: A Scenario-Aware Hybrid Planner for Closed-Loop Vehicle Trajectory Generation

Yuqi Fan, Zhiyong Cui, Zhenning Li +2

Reliable planning is crucial for achieving autonomous driving. Rule-based planners are efficient but lack generalization, while learning-based planners excel in generalization yet…

cs.CV2025

AdvReal: Physical Adversarial Patch Generation Framework for Security Evaluation of Object Detection Systems

Yuanhao Huang, Yilong Ren, Jinlei Wang +4

Autonomous vehicles are typical complex intelligent systems with artificial intelligence at their core. However, perception methods based on deep learning are extremely vulnerable…