Improve neural surface reconstruction by modeling high-frequency details with HFS

Improve neural surface reconstruction by modeling high-frequency details with HFS

Improved surface reconstruction using high-frequency details

arXiv paper abstract https://arxiv.org/abs/2206.07850v1

arXiv PDF paper https://arxiv.org/pdf/2206.07850v1.pdf

Neural rendering can be used to reconstruct implicit representations of shapes without 3D supervision.

However, current neural surface reconstruction methods have difficulty learning high-frequency details of shapes, so that the reconstructed shapes are often oversmoothed.

... improve ... surface reconstruction ... analyze the relationship between the signed distance function, the volume density, the transparency function, and the weighting function ... in the volume rendering

... decompose the signed distance function in a base function and a displacement function together with a coarse-to-fine strategy to gradually increase the high-frequency details.

... use an adaptive strategy ... focus on improving certain regions near the surface where the signed distance fields have artifacts.

... method can reconstruct high-frequency surface details and obtain better surface reconstruction quality than the current state of the art ...

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