High-fidelity 3D Model Compression based on Key Spheres. (arXiv:2201.07486v1 [cs.CV])

In recent years, neural signed distance function (SDF) has become one of the
most effectiverepresentation methods for 3D models. By learning continuous SDFs
in 3D space, neuralnetworks can predict the distance from a given query space
point to its closest object surface,whose positive and negative signs denote
inside and outside of the object, respectively.Training a specific network for
each 3D model, which individually embeds its shape, canrealize compressed
representation of objects by storing fewer network (and possibly
latent)parameters. Consequently, reconstruction …

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