Alpha Invariance: On Inverse Scaling Between Distance and Volume Density in Neural Radiance Fields
arxiv(2024)
摘要
Scale-ambiguity in 3D scene dimensions leads to magnitude-ambiguity of
volumetric densities in neural radiance fields, i.e., the densities double when
scene size is halved, and vice versa. We call this property alpha invariance.
For NeRFs to better maintain alpha invariance, we recommend 1) parameterizing
both distance and volume densities in log space, and 2) a
discretization-agnostic initialization strategy to guarantee high ray
transmittance. We revisit a few popular radiance field models and find that
these systems use various heuristics to deal with issues arising from scene
scaling. We test their behaviors and show our recipe to be more robust.
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