State of the art in surface reconstruction from point clouds
M Berger, A Tagliasacchi, LM Seversky… - … Conference of the …, 2014 - infoscience.epfl.ch
The area of surface reconstruction has seen substantial progress in the past two decades.
The traditional problem addressed by surface reconstruction is to recover the digital …
The traditional problem addressed by surface reconstruction is to recover the digital …
Learning shape templates with structured implicit functions
Template 3D shapes are useful for many tasks in graphics and vision, including fitting
observation data, analyzing shape collections, and transferring shape attributes. Because of …
observation data, analyzing shape collections, and transferring shape attributes. Because of …
Structurenet: Hierarchical graph networks for 3d shape generation
The ability to generate novel, diverse, and realistic 3D shapes along with associated part
semantics and structure is central to many applications requiring high-quality 3D assets or …
semantics and structure is central to many applications requiring high-quality 3D assets or …
Grass: Generative recursive autoencoders for shape structures
We introduce a novel neural network architecture for encoding and synthesis of 3D shapes,
particularly their structures. Our key insight is that 3D shapes are effectively characterized by …
particularly their structures. Our key insight is that 3D shapes are effectively characterized by …
A comprehensive overview of methodologies and performance evaluation frameworks in 3D mesh segmentation
P Theologou, I Pratikakis, T Theoharis - Computer Vision and Image …, 2015 - Elsevier
Abstract 3D mesh segmentation has become a crucial part of many applications in 3D shape
analysis. In this paper, a comprehensive survey on 3D mesh segmentation methods is …
analysis. In this paper, a comprehensive survey on 3D mesh segmentation methods is …
Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views
Object viewpoint estimation from 2D images is an essential task in computer vision.
However, two issues hinder its progress: scarcity of training data with viewpoint annotations …
However, two issues hinder its progress: scarcity of training data with viewpoint annotations …
A survey of surface reconstruction from point clouds
M Berger, A Tagliasacchi, LM Seversky… - Computer graphics …, 2017 - Wiley Online Library
The area of surface reconstruction has seen substantial progress in the past two decades.
The traditional problem addressed by surface reconstruction is to recover the digital …
The traditional problem addressed by surface reconstruction is to recover the digital …
SDM-NET: Deep generative network for structured deformable mesh
We introduce SDM-NET, a deep generative neural network which produces structured
deformable meshes. Specifically, the network is trained to generate a spatial arrangement of …
deformable meshes. Specifically, the network is trained to generate a spatial arrangement of …
Primal-dual mesh convolutional neural networks
Recent works in geometric deep learning have introduced neural networks that allow
performing inference tasks on three-dimensional geometric data by defining convolution …
performing inference tasks on three-dimensional geometric data by defining convolution …
Spaghetti: Editing implicit shapes through part aware generation
Neural implicit fields are quickly emerging as an attractive representation for learning based
techniques. However, adopting them for 3D shape modeling and editing is challenging. We …
techniques. However, adopting them for 3D shape modeling and editing is challenging. We …