AI RESEARCH
Rethinking Driving World Model as Synthetic Data Generator for Perception Tasks
arXiv CS.CV
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ArXi:2510.19195v4 Announce Type: replace Recent advancements in driving world models enable controllable generation of high-quality RGB videos or multimodal videos. Existing methods primarily focus on metrics related to generation quality and controllability. However, they often overlook the evaluation of downstream perception tasks, which are $\mathbf{really\ crucial}$ for the performance of autonomous driving. Existing methods usually leverage a