Get 3D object shape from one image in 45 seconds by 2D diffusion and neural surface with One-2-3-45
Get 3D object shape from one image in 45 seconds by 2D diffusion and neural surface with One-2-3-45
One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization
arXiv paper abstract https://arxiv.org/abs/2306.16928
arXiv PDF paper https://arxiv.org/pdf/2306.16928.pdf
Single image 3D reconstruction is an important but challenging task that requires extensive knowledge of ... natural world.
... propose a novel method that takes a single image of any object as input and generates a full 360-degree 3D textured mesh in a single feed-forward pass.
Given a single image ... first use a view-conditioned 2D diffusion model, Zero123, to generate multi-view images for the input view, and then aim to lift them up to 3D space.
... build ... 3D reconstruction module upon an SDF-based generalizable neural surface reconstruction method and propose several critical training strategies to enable the reconstruction of 360-degree meshes.
Without costly optimizations ... method reconstructs 3D shapes in significantly less time than existing methods.
... demonstrate its superiority in terms of both mesh quality and runtime ...
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