Editing Implicit Shapes Through Part Aware Generation

Amir Hertz

doi:10.1145/3528223.3530084

Editing Implicit Shapes Through Part Aware Generation

2022-07-22

18

OA

AI

DOI：10.1145/3528223.3530084

Original

Original request for help

Save

Abstract

En 中文

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 introduce a method for Editing Implicit Shapes Through Part Aware GeneraTion, permuted in short as SPAGHETTI. Our architecture allows for manipulation of implicit shapes by means of transforming, interpolating and combining shape segments together, without requiring explicit part supervision. SPAGHETTI disentangles shape part representation into extrinsic and intrinsic geometric information. This characteristic enables a generative framework with part-level control. The modeling capabilities of SPAGHETTI are demonstrated using an interactive graphical interface, where users can directly edit neural implicit shapes. Our code, editing user interface demo and pre-trained models are available at github.com/amirhertz/spaghetti.

Keywords:

neural networks

shape synthesis

shape modeling

Editing Implicit Shapes Through Part Aware Generation

Abstract

Journal

Organization