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Get 3D object shape using unsigned orthogonal distance fields with Lu

Get 3D object shape using unsigned orthogonal distance fields with Lu


Unsigned Orthogonal Distance Fields: An Accurate Neural Implicit Representation for Diverse 3D Shapes



Neural implicit representation of geometric shapes has witnessed considerable advancements in recent years.


... introduce a novel neural implicit representation based on unsigned orthogonal distance fields (UODFs).


In UODFs, the minimal unsigned distance from any spatial point to the shape surface is defined solely in one orthogonal direction, contrasting with the multi-directional determination made by SDF and UDF.


Consequently, every point in the 3D UODFs can directly access its closest surface points along three orthogonal directions.


This distinctive feature leverages the accurate reconstruction of surface points without interpolation errors.


... verify the effectiveness of UODFs through ... examples ... from simple watertight or non-watertight shapes to complex shapes that include hollows, internal or assembling structures.



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