4 accepted papers
Recent advances in vision language models (VLMs) have demonstrated remarkable potential in embodied navigation tasks. However, existing robot-centric datasets primarily focus on traditional 3D tasks such as perception and prediction, lacking adequate support for vision-language tasks. Vision-languag
The bird’s-eye view (BEV) representation enables multi-sensor features to be fused within a unified space, serving as the primary approach for achieving comprehensive multi-task perception. However, the discrete grid representation of BEV leads to significant detail loss and limits feature alignment…
End-to-end autonomous driving technology has recently become a focal point of research and application in autonomous driving. State-of-the-art (SOTA) methods are often trained and evaluated on the NuScenes dataset. However, the NuScenes dataset, introduced in 2019 for 3D perception tasks, faces seve…
"Vehicle-to-everything (V2X) technology has become an area of interest in research due to the availability of roadside infrastructure perception datasets. However, these datasets primarily focus on urban intersections and lack data on highway scenarios. Additionally, the perception tasks in the data…