We present a technique for adaptively partitioning neural scene representations. Our method disentangles lighting, material, and geometric information yielding a scene representation that preserves the orthogonality of these components, improves …
We describe a machine learning technique for reconstructing image sequences rendered using Monte Carlo methods. Our primary focus is on reconstruction of global illumination with extremely low sampling budgets at interactive rates. Motivated by …