English

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

Computer Vision and Pattern Recognition 2022-09-09 v4 Artificial Intelligence Computational Geometry

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.

Keywords

Cite

@article{arxiv.2109.10767,
  title  = {HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation},
  author = {Subeesh Vasu and Nicolas Talabot and Artem Lukoianov and Pierre Baqué and Jonathan Donier and Pascal Fua},
  journal= {arXiv preprint arXiv:2109.10767},
  year   = {2022}
}

Comments

18 pages, 21 figures, 3DV 2022

R2 v1 2026-06-24T06:13:12.029Z