3 papers
cs.CV2026
LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving
Chen Yang, Yuhao Wei, Ze Xu +6
Vision-Language Models (VLMs) provide powerful semantic understanding and commonsense reasoning for End-to-End Autonomous Driving (E2E-AD) planning. However, trajectories directly…
cs.RO2026
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
Qi Lan, Yining Tang, Yu Shen +4
Safety-critical traffic scenario generation is essential for evaluating autonomous driving systems under rare but high-risk interactions. Existing diffusion-based methods offer str…
cs.CV2024
DeconfuseTrack:Dealing with Confusion for Multi-Object Tracking
Cheng Huang, Shoudong Han, Mengyu He +2
Accurate data association is crucial in reducing confusion, such as ID switches and assignment errors, in multi-object tracking (MOT). However, existing advanced methods often over…