FrameTwin: Curve-Anchored Gaussian Alignment from Sparse Views for Adaptive Wireframe 3D Printing

2026-05-10

AI Summary

This work addresses the geometric inaccuracies in sparse-view filament-based wireframe 3D printing caused by deformation. We propose a Gaussian alignment framework anchored on parametric curves, which constrains Gaussian kernels to these curves to yield a compact, geometry-aware wireframe representation that substantially reduces reconstruction ambiguity under sparse observations. By integrating differentiable rendering with neural deformation field estimation, our method achieves globally consistent deformation alignment and drives the co-evolution of a digital twin model. This enables dynamic updating of printing paths within a closed-loop adaptive control system, robustly compensating for deformations during robotic wireframe fabrication and significantly enhancing both manufacturing accuracy and adaptability for complex structures.

Abstract

We present FrameTwin, a curve-anchored Gaussian alignment framework that uses sparse-view images to close the control loop for adaptive wireframe 3D printing. Our key idea is to capture the deformation of thin wireframe structures from sparse-view images using Gaussian kernels anchored to parametric curves, yielding a compact and geometry-aware encoding that explicitly captures strut topology. Driven by a differentiable rendering pipeline, FrameTwin estimates a neural deformation field that aligns the partially printed target model with the deformed structure observed during fabrication, where the optimized curve-Gaussian representation serves as a digital twin of the evolving wireframe. Unlike general Gaussian-splatting approaches, our formulation constrains kernel placement along parametric curves, substantially reducing the ambiguity inherent in sparse-view observations of thin structures. The resultant deformation-field alignment enforces global consistency across all struts. By using the estimated deformation field to blend the distorted printed geometry with the remaining unprinted geometry, FrameTwin enables adaptive updates to future printing trajectories. We demonstrate that FrameTwin can robustly capture and compensate for deformation in wireframe models fabricated using a robotized 3D printing system.

Problem

• wireframe 3D printing
• deformation compensation
• sparse-view reconstruction
• adaptive fabrication
• thin structures

Innovation

• curve-anchored Gaussian
• sparse-view alignment
• adaptive wireframe 3D printing
• neural deformation field
• digital twin