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.

翻译：三维场景维度的尺度模糊性会导致神经辐射场中体积密度存在量级模糊性，即场景尺寸减半时密度加倍，反之亦然。我们将这一特性称为Alpha不变性。为使NeRF更好地维持Alpha不变性，我们建议：1）在对数空间中参数化距离与体积密度；2）采用离散化无关的初始化策略以确保光线具有高透射率。通过重新审视若干主流辐射场模型，我们发现这些系统采用不同的启发式方法处理场景缩放引发的问题。通过行为对比测试，验证了本方法具有更强的鲁棒性。