Learning Unsigned Distance Fields from Local Shape Functions for 3D
Surface Reconstruction
Learning Unsigned Distance Fields from Local Shape Functions for 3D
Surface Reconstruction
Unsigned distance fields (UDFs) provide a versatile framework for representing a diverse array of 3D shapes, encompassing both watertight and non-watertight geometries. Traditional UDF learning methods typically require extensive training on large datasets of 3D shapes, which is costly and often necessitates hyperparameter adjustments for new datasets. This paper presents …