Grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, grid-centric perception is less prevalent than object-centric perception for …

End-to-end autonomous driving has made impressive progress in recent years. Existing
methods usually adopt the decoupled encoder-decoder paradigm, where the encoder …

Abstract 3D object detection is an important task in autonomous driving to perceive the
surroundings. Despite the excellent performance, the existing 3D detectors lack the …

False negatives (FN) in 3D object detection, eg, missing predictions of pedestrians, vehicles,
or other obstacles, can lead to potentially dangerous situations in autonomous driving. While …

Diverse transport demands have resulted in the wide existence of heterogeneous vehicle
automation systems. While these systems have demonstrated effectiveness, they also pose …

Abstract View Transformation Module (VTM), where transformations happen between multi-
view image features and Bird-Eye-View (BEV) representation, is a crucial step in camera …

We study how vision-language models (VLMs) trained on web-scale data can be integrated
into end-to-end driving systems to boost generalization and enable interactivity with human …

End-to-end autonomous driving recently emerged as a promising research direction to
target autonomy from a full-stack perspective. Along this line many of the latest works follow …

Abstract 3D object detection is an essential perception task in autonomous driving to
understand the environments. The Bird's-Eye-View (BEV) representations have significantly …

In contrast to extensive studies on general vision pre-training for scalable visual
autonomous driving remains seldom explored. Visual autonomous driving applications …