Unlike opaque object, novel view synthesis of transparent object is a
challenging task, because transparent object refracts light of background
causing visual distortions on the transparent object surface along the
viewpoint change. Recently introduced Neural Radiance Fields (NeRF) is a view
synthesis method. Thanks to its remarkable performance improvement, lots of
following applications based on NeRF in various topics have been developed.
However, if an object with a different refractive index is included in a scene
such as transparent object, NeRF shows limited performance because refracted
light ray at the surface of the transparent object is not appropriately
considered. To resolve the problem, we propose a NeRF-based method consisting
of the following three steps: First, we reconstruct a three-dimensional shape
of a transparent object using visual hull. Second, we simulate the refraction
of the rays inside of the transparent object according to Snell's law. Last, we
sample points through refracted rays and put them into NeRF. Experimental
evaluation results demonstrate that our method addresses the limitation of
conventional NeRF with transparent objects.

我们提出了一种基于 NeRF 的方法，通过三个步骤解决了传统 NeRF 在透明对象方面的局限性。首先，使用可视外形重建透明对象的三维形状。其次，根据斯涅尔定律模拟透明对象内部的光线折射。最后，通过折射光线采样点，并将其放入 NeRF 中。实验结果表明，我们的方法解决了传统 NeRF 在处理透明对象方面的限制。