Image segmentation, which has become a research hotspot in the field of image processing
and computer vision, refers to the process of dividing an image into meaningful and non …

This paper surveys mesh segmentation techniques and algorithms, with a focus on part‐
based segmentation, that is, segmentation that divides a mesh (featuring a 3D object) into …

This paper presents a new deep learning architecture called PointGrid that is designed for
3D model recognition from unorganized point clouds. The new architecture embeds the …

In this paper, we present a novel approach for 3D dental model segmentation via deep
Convolutional Neural Networks (CNNs). Traditional geometry-based methods tend to …

This paper describes a benchmark for evaluation of 3D mesh segmentation salgorithms. The
benchmark comprises a data set with 4,300 manually generated segmentations for 380 …

This paper presents a data-driven approach to simultaneous segmentation and labeling of
parts in 3D meshes. An objective function is formulated as a Conditional Random Field …

Most attempts to represent 3D shapes for deep learning have focused on volumetric grids,
multi-view images and point clouds. In this paper we look at the most popular representation …

One of the core tasks in social network analysis is to predict the formation of links (ie various
types of relationships) over time. Previous research has generally represented the social …

The goal of this paper is to investigate a new shape analysis method based on randomized
cuts of 3D surface meshes. The general strategy is to generate a random set of mesh …

Recently, the emergence of diffusion models has opened up new opportunities for single-
view reconstruction. However, all the existing methods represent the target object as a …