Appearance-Preserving Refinement of Generated 3D Assets for Monochromatic Fabrication

2026-06-25

AI Summary

This work addresses the challenge in monochromatic fabrication where the absence of texture information leads to visually impoverished 3D assets, while directly encoding texture into geometry often induces stress concentrations and manufacturing failure. To reconcile visual fidelity with structural robustness, we propose GenMF—a novel framework that introduces, for the first time, a differentiable stress-aware regularization mechanism coupled with a learning-based thermal stress predictor. By integrating differentiable rendering, thermo-mechanical simulation, and appearance-preserving geometry optimization, our method translates texture-induced shading cues into geometric detail without compromising manufacturability. Evaluated under monochromatic rendering, GenMF significantly enhances visual realism while reducing mechanical stress. Physical 3D prints validate that the generated geometries retain recognizable visual features and exhibit excellent printability.

Abstract

Recent advances in 3D mesh generation have enabled the creation of visually realistic assets. However, much of their visual fidelity is encoded in textures rather than geometry. When such assets are fabricated using monochromatic materials, texture information is largely lost, causing visually important details to disappear even when the original geometry is faithfully preserved. A key challenge is that the geometric perturbations required to recover texture-dependent appearance cues often introduce sharp local features and high-frequency surface structures, which may increase stress concentration and fabrication risk. In this paper, we present GenMF, an appearance-oriented geometry refinement framework for monochromatic fabrication. GenMF transforms texture-dependent visual cues into geometry-induced shading effects and formulates geometry refinement as a balance between appearance preservation and fabrication-oriented robustness. To discourage structurally and narrow the gap between simulation and physical manufacturing, we further introduce a differentiable stress-aware regularization based on a learned thermal-stress predictor. Experimental results demonstrate that GenMF significantly improves appearance preservation under monochromatic rendering while reducing stress concentration under a consistent thermo-mechanical simulation setting. Physical 3D printing examples further show that the refined geometries preserve more recognizable visual details while remaining suitable for fabrication. These results suggest that appearance-aware geometry refinement provides an effective bridge between generated 3D assets and fabrication-ready monochromatic objects.

Problem

• monochromatic fabrication
• appearance preservation
• geometry refinement
• stress concentration
• 3D asset generation

Innovation

• appearance-preserving geometry
• monochromatic fabrication
• stress-aware regularization
• differentiable rendering
• 3D asset refinement