Superpixels group perceptually similar pixels to create visually meaningful entities while
heavily reducing the number of primitives for subsequent processing steps. As of these …

We present an improved version of the Simple Linear Iterative Clustering (SLIC) superpixel
segmentation. Unlike SLIC, our algorithm is non-iterative, enforces connectivity from the …

In this paper, we propose a real-time image superpixel segmentation method with 50
frames/s by using the density-based spatial clustering of applications with noise (DBSCAN) …

In this paper, we present a superpixel segmentation algorithm called linear spectral
clustering (LSC), which is capable of producing superpixels with both high boundary …

We propose a new approach for semantic segmentation of 3D city models. Starting from an
SfM reconstruction of a street-side scene, we perform classification and facade splitting …

Automated 3D reconstruction based on satellite images has become a research hotspot at
the interdisciplinary of photogrammetry and computer vision. The 3D results based on …

Albeit remarkable progress has been made to improve the accuracy and completeness of
multi-view stereo (MVS), existing methods still suffer from either sparse reconstructions of …

Recently, some approaches are proposed to harness deep convolutional networks to
facilitate superpixel segmentation. The common practice is to first evenly divide the image …

Superpixel segmentation targets at grouping pixels in an image into atomic regions whose
boundaries align well with the natural object boundaries. This paper first proposes a new …

Converting point clouds generated by Laser scanning, multiview stereo imagery or depth
cameras into compact polygon meshes is a challenging problem in vision. Existing methods …