Physically-Motivated Learning of Shape, Material and Lighting in Complex Scenes

Physically-Motivated Learning of Shape, Material and Lighting in Complex Scenes

Explore a comprehensive talk on physically-motivated learning for shape, material, and lighting recovery in complex scenes. Delve into the challenges of inverse rendering and image formation, examining novel approaches that combine deep learning with physical insights. Learn about differentiable rendering layers, parsimonious representations, and synthetic datasets that enable applications in augmented reality and scene editing. Discover how these techniques can transform mobile phones into accessible AR devices, and gain insights into spatially-varying lighting estimation, object insertion, and material editing using single unconstrained images.