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Unsigned Orthogonal Distance Fields: An Accurate Neural Implicit Representation for Diverse 3D Shapes
The author introduces Unsigned Orthogonal Distance Fields (UODFs) as a novel neural implicit representation for accurate reconstruction of diverse 3D shapes. UODFs offer unique characteristics that differentiate them from traditional Signed Distance Fields (SDF) and Unsigned Distance Fields (UDF), leading to improved reconstruction accuracy.
Unsigned Orthogonal Distance Fields: An Accurate Neural Implicit Representation for Diverse 3D Shapes
UODFs provide accurate reconstruction of diverse 3D shapes through unique characteristics and neural networks.
Unsigned Orthogonal Distance Fields: An Accurate Neural Implicit Representation for Diverse 3D Shapes
UODFs provide accurate reconstruction for diverse 3D shapes through unique characteristics and specialized neural networks.
