The Flow has not summarised this story yet — read it at arXiv Computer Vision.
arXiv:2609.07511v1 Announce Type: cross Abstract: Autonomous driving relies on High Definition (HD) maps for safe navigation. Traditional HD maps construction is costly in hardware, data and human re...
arXiv:2610.01905v1 Announce Type: new Abstract: Online vectorized HD map construction is essential for scaling safe autonomous driving and requires accurate, real-time inference. Prior methods typica...
arXiv:2609.22868v1 Announce Type: new Abstract: End-to-end driving requires planning-relevant bird's-eye-view (BEV) representations, but existing pretraining approaches often rely on task annotations...
arXiv:2606. 17080v1 Announce Type: cross Abstract: Reliable autonomous driving requires vectorized HD maps that are geometrically accurate, semantically rich, and scalable to long-horizon driving.
arXiv:2606. 21165v2 Announce Type: replace-cross Abstract: We present OmniV2X, a generative foundation model for vehicle-to-everything (V2X) cooperative driving.
arXiv:2608.28672v1 Announce Type: cross Abstract: Autonomous vehicles operate in dynamic, ever-changing environments where new scenarios and edge cases constantly emerge. As a result, static learning...