Neural Relighting with Subsurface Scattering by Learning the Radiance
  Transfer Gradient
Reconstructing and relighting objects and scenes under varying lighting
conditions is challenging: existing neural rendering methods often cannot
handle the complex interactions between materials and light. Incorporating
pre-computed radiance transfer techniques enables global illumination, but
still struggles with materials with subsurface scattering effects. We propose a
novel framework for learning the radiance transfer field via volume rendering
and utilizing various appearance cues to refine geometry end-to-end. This
framework extends relighting and reconstruction capabilities to handle a wider
range of materials in a data-driven fashion. The resulting models produce
plausible rendering results in existing and novel conditions. We will release
our code and a novel light stage dataset of objects with subsurface scattering
effects publicly available.
648c000c5bfc81b14f4b771f
Shizhan Zhu
648c000c5bfc81b14f4b7720
Shunsuke Saito
admin_assigned
2023-06-19T11:50:06.742Z
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/avatars/1681e465d7649f67f94e1b69d236cb1e.svg
Shunsuke Saito
user
psyth
648c000c5bfc81b14f4b7721
Aljaz Bozic
648c000c5bfc81b14f4b7722
Carlos Aliaga
648c000c5bfc81b14f4b7723
Trevor Darrell
648c000c5bfc81b14f4b7724
Christop Lassner
Neural Relighting with Subsurface Scattering by Learning the Radiance
  Transfer Gradient
Reconstructing and relighting objects and scenes under varying lighting
conditions is challenging: existing neural rendering methods often cannot
handle the complex interactions between materials and light. Incorporating
pre-computed radiance transfer techniques enables global illumination, but
still struggles with materials with subsurface scattering effects. We propose a
novel framework for learning the radiance transfer field via volume rendering
and utilizing various appearance cues to refine geometry end-to-end. This
framework extends relighting and reconstruction capabilities to handle a wider
range of materials in a data-driven fashion. The resulting models produce
plausible rendering results in existing and novel conditions. We will release
our code and a novel light stage dataset of objects with subsurface scattering
effects publicly available.
A novel framework for learning radiance transfer using volume rendering and appearance cues improves rendering and relighting of complex materials, including subsurface scattering.
radiance transfer volume rendering appearance cues global illumination subsurface scattering RenderNet