Log In Sign Up

Nonwatertight Mesh Reconstruction

by   Partha Ghosh, et al.

Reconstructing 3D non-watertight mesh from an unoriented point cloud is an unexplored area in computer vision and computer graphics. In this project, we tried to tackle this problem by extending the learning-based watertight mesh reconstruction pipeline presented in the paper 'Shape as Points'. The core of our approach is to cast the problem as a semantic segmentation problem that identifies the region in the 3D volume where the mesh surface lies and extracts the surfaces from the detected regions. Our approach achieves compelling results compared to the baseline techniques.


page 9

page 10

page 13


Voxel Structure-based Mesh Reconstruction from a 3D Point Cloud

Mesh reconstruction from a 3D point cloud is an important topic in the f...

MeshNet: Mesh Neural Network for 3D Shape Representation

Mesh is an important and powerful type of data for 3D shapes and widely ...

Semantic Segmentation of Surface from Lidar Point Cloud

In the field of SLAM (Simultaneous Localization And Mapping) for robot n...

Hierarchical Detail Enhancing Mesh-Based Shape Generation with 3D Generative Adversarial Network

Automatic mesh-based shape generation is of great interest across a wide...

Z2P: Instant Rendering of Point Clouds

We present a technique for rendering point clouds using a neural network...

An Intrinsic Geometrical Approach for Statistical Process Control of Surface and Manifold Data

This paper presents a new method for statistical process control (SPC) o...

Point Scene Understanding via Disentangled Instance Mesh Reconstruction

Semantic scene reconstruction from point cloud is an essential and chall...