Neural Radiance Fields for Transparent Object Using Visual Hull

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 method based on NeRF, mathematical equations for the description of light refraction, and visual hull. Experimental evaluation results demonstrate that our method addresses the limitation of conventional NeRF with transparent objects.