Poxel: Voxel Reconstruction for 3D Printing
원문 초록
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.
함께 살펴볼 논문
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R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimation
MCN-SLAM: Multi-Agent Collaborative Neural SLAM with Hybrid Implicit Neural Scene Representation
Unifying Appearance Codes and Bilateral Grids for Driving Scene Gaussian Splatting
PhysicsNeRF: Physics-Guided 3D Reconstruction from Sparse Views
GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis
토론
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