Line segment detectors with deformable attention

Abstract

The object detectors based on Transformers are advancing rapidly. On the contrary, the development of line segment detectors is relatively slow. It is noteworthy that the object and line segments are both 2D targets. In this work, we design a line segment detection algorithm based on deformable attention. Leveraging this algorithm and the line segment loss function, we transform the object detectors, Deformable DETR and ViDT, into end-to-end line segment detectors named Deformable LETR and ViDTLE, respectively. In order to adapt the idea of sparse modeling for line segment detection, we propose a new attention mechanism named line segment deformable attention (LSDA). This mechanism focuses on the valuable positions under the guidance of reference line to refine line segments. We design an auxiliary algorithm named line segment iterative refinement for LSDA. With as few modifications as possible, we transform two object detection detectors, namely SMCA DETR and PnP DETR into competitive line segment detectors named SMCA LETR and PnP LETR, respectively. The experimental results show that the performances of the proposed methods are efficient.