Rendering refers to a process of creating digital images of an object or a scene from 3D data using computers and algorithms. Inverse rendering is the inverse process of rendering, i.e., reconstructing 3D data from 2D images. The 3D data to be recovered can be 3D geometry, reflectance of a surface, camera viewpoints, or lighting conditions.
In this talk, we will discuss three inverse rendering problems. First, inverse rendering using flash photography captures 3D geometry and reflectance of a static object using a single camera and a flashlight attached to the camera. An alternating and iterative optimization framework is proposed to jointly solve for several unknown properties. Second, inverse rendering at microscale reconstructs 3D normals and reflectance of a surface at microscale. A specially designed acquisition system, as well as an inverse rendering algorithm for microscale material appearance, are proposed. Lastly, inverse rendering for human hair describes a novel 3D reconstruction algorithm for modeling high-quality human hair geometry. We hope that our work on these advanced inverse rendering problems boosts hyper-realism in computer graphics
Giljoo Nam received his Ph.D. from KAIST in August 2019. His doctoral research focuses on inverse rendering for realistic computer graphics. In particular, he has been working on high-quality 3D reconstruction and material appearance modeling. His research on image-based appearance modeling was selected as a representative achievement at ACM SIGGRAPH Asia 2018, receiving press attention from various notable media (e.g., EurekAlert, ScienceDaily, SciTech). He is also a recipient of KCGS (Korea Computer Graphics Society) Young Researcher Award and SIGGRAPH Doctoral Consortium Award. He is currently working as a technical consultant for research institutes in Korea.