Get 3D shape of object using material and lighting estimates and physics rendering with Neural-PBIR
Get 3D shape of object using material and lighting estimates and physics rendering with Neural-PBIR
Neural-PBIR Reconstruction of Shape, Material, and Illumination
arXiv paper abstract https://arxiv.org/abs/2304.13445
arXiv PDF paper https://arxiv.org/pdf/2304.13445.pdf
Reconstructing the shape and spatially varying surface appearances of a physical-world object as well as its surrounding illumination based on 2D images (e.g., photographs) of the object has been a long-standing problem in computer vision and graphics.
... introduce a robust object reconstruction pipeline combining neural based object reconstruction and physics-based inverse rendering (PBIR).
... pipeline firstly leverages a neural stage to produce high-quality but potentially imperfect predictions of object shape, reflectance, and illumination.
... later stage, initialized by the neural predictions, ... perform PBIR to refine the initial results and obtain the final high-quality reconstruction.
... demonstrate ... pipeline significantly outperforms existing reconstruction methods quality-wise and performance-wise.
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