Line Segment Detection
20 papers with code • 2 benchmarks • 6 datasets
This paper presents a very simple but efficient algorithm for 3D line segment detection from large scale unorganized point cloud.
Targeting at the unified line segment detection (ULSD) for both distorted and undistorted images, we propose to represent line segments with the Bezier curve model.
In this paper, we present a joint end-to-end line segment detection algorithm using Transformers that is post-processing and heuristics-guided intermediate processing (edge/junction/region detection) free.
In this paper, we propose a real-time and light-weight line segment detector for resource-constrained environments named Mobile LSD (M-LSD).
In experiments, our method is tested on the WireFrame dataset and the YorkUrban dataset with state-of-the-art performance obtained.
Combined with high-level semantics, Sem-LS is more robust under cluttered environment compared with existing line-shaped representations.