Decoder Generates Manufacturable Structures: A Framework for 3D-Printable Object Synthesis

Fuente: arXiv
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Autor principal: Kumar, Abhishek
Formato: Preprint
Publicado: 2026
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author Kumar, Abhishek
author_facet Kumar, Abhishek
contents This paper presents a novel decoder-based approach for generating manufacturable 3D structures optimized for additive manufacturing. We introduce a deep learning framework that decodes latent representations into geometrically valid, printable objects while respecting manufacturing constraints such as overhang angles, wall thickness, and structural integrity. The methodology demonstrates that neural decoders can learn complex mapping functions from abstract representations to valid 3D geometries, producing parts with significantly improved manufacturability compared to naive generation approaches. We validate the approach on diverse object categories and demonstrate practical 3D printing of decoder-generated structures.
format Preprint
id arxiv_https___arxiv_org_abs_2601_08015
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Decoder Generates Manufacturable Structures: A Framework for 3D-Printable Object Synthesis
Kumar, Abhishek
Computer Vision and Pattern Recognition
68T45, 68U05
I.2.6; I.4.8; I.3.5
This paper presents a novel decoder-based approach for generating manufacturable 3D structures optimized for additive manufacturing. We introduce a deep learning framework that decodes latent representations into geometrically valid, printable objects while respecting manufacturing constraints such as overhang angles, wall thickness, and structural integrity. The methodology demonstrates that neural decoders can learn complex mapping functions from abstract representations to valid 3D geometries, producing parts with significantly improved manufacturability compared to naive generation approaches. We validate the approach on diverse object categories and demonstrate practical 3D printing of decoder-generated structures.
title Decoder Generates Manufacturable Structures: A Framework for 3D-Printable Object Synthesis
topic Computer Vision and Pattern Recognition
68T45, 68U05
I.2.6; I.4.8; I.3.5
url https://arxiv.org/abs/2601.08015