Get 3D object from monocular RGB-D video using diffusion prior with MorpheuS
Get 3D object from monocular RGB-D video using diffusion prior with MorpheuS
MorpheuS: Neural Dynamic 360° Surface Reconstruction from Monocular RGB-D Video
arXiv paper abstract https://arxiv.org/abs/2312.00778
arXiv PDF paper https://arxiv.org/pdf/2312.00778.pdf
… neural representations … can accurately capture the motion and achieve high-fidelity reconstruction of the target object.
Despite this, real-world video scenarios often feature large unobserved regions where neural representations struggle to achieve realistic completion.
… introduce MorpheuS, a framework for dynamic 360° surface reconstruction from a casually captured RGB-D video
… models the target scene as a canonical field that encodes its geometry and appearance, in conjunction with a deformation field that warps points from the current frame to the canonical space.
… leverage a view-dependent diffusion prior and distill knowledge from it to achieve realistic completion of unobserved regions.
… method can achieve high-fidelity 360° surface reconstruction of a deformable object from a monocular RGB-D video.
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