Talk Abstract: Neural rendering has advanced at outstanding speed in recent years, with the advent of Neural Radiance Fields, typically based on volumetric ray-marching, as well as (3D) generative models. In this talk, we investigate alternative approaches building on the explicit use of geometry to guide neural renderers, both for captured and synthetic scenes. After a brief overview of 20+ years of research in image-based and realistic rendering, we will present recent work on neural rendering methods, in particular showing how point-based splatting solutions provide very competitive alternatives to volumetric rendering, and how neural rendering can be used to provide interactive global illumination for dynamic scenes and how generative neural methods can be used to create and edit mesh-scale texture. We will conclude the talk with perspectives on neural rendering both for synthetic and captured content.

Speaker Biographies:

George Drettakis graduated in Computer Science from the University of Crete, Greece, and obtained an M.Sc.and a Ph.D., (1994) at the University of Toronto, with E. Fiume. After an ERCIM postdoc in Grenoble, Barcelona and Bonn, he obtained a Inria researcher position in Grenoble in 1995, and his "Habilitation" at the University of Grenoble (1999). He then founded the REVES research group at INRIA Sophia-Antipolis, and now heads the follow-up group GRAPHDECO and is a INRIA Senior Researcher (full professor equivalent). He received the Eurographics (EG) Outstanding Technical Contributions award in 2007 and the prestigious ERC Advanced Grant in 2019 and is an EG fellow. He was an associate editor for ACM Trans. on Graphics, technical papers chair of SIGGRAPH Asia 2010, co-chair of Eurographics IPC 2002 & 2008, associate editor and co-editor in chief of IEEE Trans. on Computer Graphics and Visualization and chairs the EG working group on Rendering (EGSR). He has worked on many different topics in computer graphics, with an emphasis on rendering. He initially concentrated on lighting and shadow computation and subsequently worked on 3D audio, perceptually-driven algorithms, virtual reality and 3D interaction. He has worked on textures, weathering and perception for graphics and in recent years on image-based and neural rendering/relighting as well as deep material acquisition.

Georgios Kopanas graduated with a Master's degree in Computer Science from the University of Thessaly. He interned at SRI International where he worked in unsupervised object detection. Later he joined Inria as an intern and a research engineer contributing to multiple projects. He then worked on drivers for mobile GPUs at ARM as a Software Engineer. In 2020, he returned to Inria as a PhD candidate under G.Drettakis, where he focused on point-based representations for Novel View Synthesis, and he is one of the lead authors of the SIGGRAPH best paper award "3D Gaussian Splatting for Real-Time Radiance Field Rendering."