HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation

TL;DR

HybridSDF introduces a novel 3D shape representation that combines deep implicit surfaces with geometric primitives, enabling effective modeling and manipulation of both complex and regular manufactured objects.

Contribution

It proposes a combined latent-explicit parameterization that integrates deep implicit shapes with geometric primitives for improved 3D shape modeling.

Findings

Effective modeling of regular and complex shapes

Enhanced shape manipulation capabilities

Consistent implicit and explicit shape representations

Abstract

Deep implicit surfaces excel at modeling generic shapes but do not always capture the regularities present in manufactured objects, which is something simple geometric primitives are particularly good at. In this paper, we propose a representation combining latent and explicit parameters that can be decoded into a set of deep implicit and geometric shapes that are consistent with each other. As a result, we can effectively model both complex and highly regular shapes that coexist in manufactured objects. This enables our approach to manipulate 3D shapes in an efficient and precise manner.