Get 3D object shape with using surface mesh and implicit signed distance field with Sur2f
Get 3D object shape with using surface mesh and implicit signed distance field with Sur2f
Sur2f: A Hybrid Representation for High-Quality and Efficient Surface Reconstruction from Multi-view Images
arXiv paper abstract https://arxiv.org/abs/2401.03704
arXiv PDF paper https://arxiv.org/pdf/2401.03704.pdf
Project page https://huang-zhangjin.github.io/project-pages/sur2f.html
Multi-view surface reconstruction is an ill-posed, inverse problem in 3D vision research … Most … rely either on … surface rendering of meshes … or implicit field functions, using volume rendering
… propose a new hybrid representation, termed Sur2f, aiming to better benefit from both representations in a complementary manner.
… learn two parallel streams of an implicit signed distance field and an explicit surrogate surface Sur2f mesh, and unify volume rendering of the implicit signed distance function (SDF) and surface rendering of the surrogate mesh with a shared, neural shader; the unified shading promotes their convergence to the same, underlying surface.
… synchronize learning of the surrogate mesh by driving its deformation with functions induced from the implicit SDF.
… synchronized surrogate mesh enables surface-guided volume sampling, which greatly improves the sampling efficiency per ray in volume rendering.
… Sur2f outperforms existing reconstruction methods and surface representations, including hybrid ones, in terms of both recovery quality and recovery efficiency.
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