IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes. (arXiv:2206.08423v1 [cs.CV])

Indoor scenes exhibit significant appearance variations due to myriad
interactions between arbitrarily diverse object shapes, spatially-changing
materials, and complex lighting. Shadows, highlights, and inter-reflections
caused by visible and invisible light sources require reasoning about
long-range interactions for inverse rendering, which seeks to recover the
components of image formation, namely, shape, material, and lighting. In this
work, our intuition is that the long-range attention learned by transformer
architectures is ideally suited to solve longstanding challenges in
single-image inverse rendering. We demonstrate …

arxiv cv image inverse rendering transformers vision