I'm interested in computer vision, deep learning, generative AI, and image processing. Most of my research is about inferring the physical world (shape, motion, color, light, etc) from images, usually with radiance fields. Some papers are highlighted.
Parameterizing a scene with a Delaunay tetrahedralization and a neural field yields a scene representation that is accurate, fast to render, easy to edit, and backwards-compatible.
A more physically-accurate inverse rendering system based on radiance caching for recovering geometry, materials, and lighting from RGB images of an object or scene.