Abstract:
In this presentation, I will talk about some of the recent work we did on new methods for reconstructing models of real world scenes from sparse or even monocular video data. These methods are based on bringing together neural network-based and explicit model-based approaches. I will also talk about new neural rendering approaches that combine explicit model-based and neural network based concepts for image formation in new ways. Together, the research presented shows new ways to reconstruct highly detailed models of humans, as well as static and dynamic real world scenes. It also paves the way for new ways to synthesize highly realistic imagery and videos of human actors and real world scenes. This opens up new possibilities, for instance, in computer graphics and computer animation, future VR and AR experiences, telepresence, but also future intelligent systems that need to perceive the real world to be able to effectively and safely act and interact in it. If time permits, I will briefly show applications of our research in Hollywood movie productions.

Bio:
Christian Theobalt is The Scientific Director of the new Visual Computing and Artificial Intelligence Department at the Max-Planck-Institute for Informatics, Saarbrücken, Germany. He is also a Professor of Computer Science at Saarland University, Germany. From 2007 until 2009 he was a Visiting Assistant Professor in the Department of Computer Science at Stanford University. He received his MSc degree in Artificial Intelligence from the University of Edinburgh, his Diplom (MS) degree in Computer Science from Saarland University, and his PhD (Dr.-Ing.) from the Max-Planck-Institute for Informatics. In his research he looks at algorithmic problems that lie at the intersection of Computer Graphics, Computer Vision and Machine Learning, such as: static and dynamic 3D scene reconstruction, neural rendering and neural scene representations, marker-less motion and performance capture, virtual humans, virtual and augmented reality, computer animation, intrinsic video and inverse rendering, computational videography, machine learning for graphics and vision, new sensors for 3D acquisition, as well as image- and physically-based rendering. He is also interested in using reconstruction techniques for human computer interaction. For his work, he received several awards, including the Otto Hahn Medal of the Max-Planck Society in 2007, the EUROGRAPHICS Young Researcher Award in 2009, the German Pattern Recognition Award 2012, the Karl Heinz Beckurts Award in 2017, and the EUROGRAPHICS Outstanding Technical Contributions Award in 2020. He is a Fellow of ELLIS and EUROGRPAHICS. He received two ERC grants, an ERC Starting Grant in 2013 and an ERC Consolidator Grant in 2017. Christian is co-founder of the Captury which is offering a world leading technology for marker-less human motion capture.