Poxel: Voxel Reconstruction for 3D Printing
This addresses the challenge of creating high-resolution, full-color 3D printable models for applications in manufacturing and design, representing an incremental improvement over existing digital-focused methods.
The paper tackles the problem of adapting 3D reconstruction methods like NeRF and Plenoxel for physical 3D printing by introducing Poxel, a voxel-based framework that removes view-dependency and converts RGB to CMYKWCl color space, achieving better fidelity and quality in printed models.
Recent advancements in 3D reconstruction, especially through neural rendering approaches like Neural Radiance Fields (NeRF) and Plenoxel, have led to high-quality 3D visualizations. However, these methods are optimized for digital environments and employ view-dependent color models (RGB) and 2D splatting techniques, which do not translate well to physical 3D printing. This paper introduces "Poxel", which stands for Printable-Voxel, a voxel-based 3D reconstruction framework optimized for photopolymer jetting 3D printing, which allows for high-resolution, full-color 3D models using a CMYKWCl color model. Our framework directly outputs printable voxel grids by removing view-dependency and converting the digital RGB color space to a physical CMYKWCl color space suitable for multi-material jetting. The proposed system achieves better fidelity and quality in printed models, aligning with the requirements of physical 3D objects.