BezierFormer: A Unified Architecture for 2D and 3D Lane Detection

arXiv:2404.16304v1 Announce Type: new
Abstract: Lane detection has made significant progress in recent years, but there is not a unified architecture for its two sub-tasks: 2D lane detection and 3D lane detection. To fill this gap, we introduce B\'{e}zierFormer, a unified 2D and 3D lane detection architecture based on B\'{e}zier curve lane representation. B\'{e}zierFormer formulate queries as B\'{e}zier control points and incorporate a novel B\'{e}zier curve attention mechanism. This attention mechanism enables comprehensive and accurate feature extraction for slender lane …

abstract architecture arxiv cs.cv detection gap lane detection progress tasks type unified architecture