Learning quadrangulated patches for 3D shape parameterization and completion

09/20/2017
by   Kripasindhu Sarkar, et al.
0

We propose a novel 3D shape parameterization by surface patches, that are oriented by 3D mesh quadrangulation of the shape. By encoding 3D surface detail on local patches, we learn a patch dictionary that identifies principal surface features of the shape. Unlike previous methods, we are able to encode surface patches of variable size as determined by the user. We propose novel methods for dictionary learning and patch reconstruction based on the query of a noisy input patch with holes. We evaluate the patch dictionary towards various applications in 3D shape inpainting, denoising and compression. Our method is able to predict missing vertices and inpaint moderately sized holes. We demonstrate a complete pipeline for reconstructing the 3D mesh from the patch encoding. We validate our shape parameterization and reconstruction methods on both synthetic shapes and real world scans. We show that our patch dictionary performs successful shape completion of complicated surface textures.

READ FULL TEXT
research
03/25/2019

Learning Quadrangulated Patches For 3D Shape Processing

We propose a system for surface completion and inpainting of 3D shapes u...
research
06/10/2022

PatchComplete: Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories

While 3D shape representations enable powerful reasoning in many visual ...
research
11/25/2019

Shape Reconstruction by Learning Differentiable Surface Representations

Generative models that produce point clouds have emerged as a powerful t...
research
12/11/2019

BINet: a binary inpainting network for deep patch-based image compression

Recent deep learning models outperform standard lossy image compression ...
research
09/30/2017

Robust Surface Reconstruction from Gradients via Adaptive Dictionary Regularization

This paper introduces a novel approach to robust surface reconstruction ...
research
02/21/2022

Computational Pattern Making from 3D Garment Models

We propose a method for computing a sewing pattern of a given 3D garment...
research
09/21/2018

Adaptive O-CNN: A Patch-based Deep Representation of 3D Shapes

We present an Adaptive Octree-based Convolutional Neural Network (Adapti...

Please sign up or login with your details

Forgot password? Click here to reset