IntrinsicAnything: Learning Diffusion Priors for Inverse Rendering Under Unknown Illumination

arXiv:2404.11593v1 Announce Type: new
Abstract: This paper aims to recover object materials from posed images captured under an unknown static lighting condition. Recent methods solve this task by optimizing material parameters through differentiable physically based rendering. However, due to the coupling between object geometry, materials, and environment lighting, there is inherent ambiguity during the inverse rendering process, preventing previous methods from obtaining accurate results. To overcome this ill-posed problem, our key idea is to learn the material prior with a …

arxiv cs.cv diffusion inverse rendering rendering type