LightOctree: Lightweight 3D Spatially-Coherent Indoor Lighting
  Estimation
Xuecan Wang Shibang Xiao Xiaohui Liang
We present a lightweight solution for estimating spatially-coherent indoor
lighting from a single RGB image. Previous methods for estimating illumination
using volumetric representations have overlooked the sparse distribution of
light sources in space, necessitating substantial memory and computational
resources for achieving high-quality results. We introduce a unified, voxel
octree-based illumination estimation framework to produce 3D spatially-coherent
lighting. Additionally, a differentiable voxel octree cone tracing rendering
layer is proposed to eliminate regular volumetric representation throughout the
entire process and ensure the retention of features across different frequency
domains. This reduction significantly decreases spatial usage and required
floating-point operations without substantially compromising precision.
Experimental results demonstrate that our approach achieves high-quality
coherent estimation with minimal cost compared to previous methods.