Dr. Justus Thies is working as a postdoctoral researcher at the Technical University of Munich (TUM). In September 2017 he joined the Visual Computing Lab of Prof.Dr. Matthias Nießner. Previous, he was a PhD student at the University of Erlangen-Nuremberg under the supervision of Günther Greiner. He started his PhD studies in 2014 after receiving his Master of Science degree from the University of Erlangen-Nuremberg. During the time as a PhD student he collaborated with other institutes and did internships at Stanford University and the Max-Planck-Institute for Informatics. His research focuses on real-time facial performance capturing and expression transfer using commodity hardware. Thus, he is interested in Computer Vision and Computer Graphics, as well as in efficient implementations of optimization techniques, especially on graphics hardware. His publications opened up a new research field - real-time facial reenactment. The achieved quality, efficiency and the reduced hardware requirements of his developed methods raised a lot of attention in academia, industry and media. The dissertation "Face2Face: Real-time Facial Reenactment" of Justus Thies summarizes these publications and discusses the implications of the demonstrated technologies.
Website: https://justusthies.github.io/
Dr. Michael Zollhöfer is a Visiting Assistant Professor at Stanford University. His stay at Stanford is funded by a postdoctoral fellowship of the Max Planck Center for Visual Computing and Communication (MPC-VCC), which he received for his work in the fields of computer vision, computer graphics, and machine learning. Before, Michael was a Postdoctoral Researcher in the Graphics, Vision & Video' group at the Max Planck Institute for Informatics in Saarbrücken, Germany. He received his PhD in 2014 from the University of Erlangen-Nuremberg for his work on real-time static and dynamic scene reconstruction. His research is focused on teaching computers to reconstruct and analyze our world at frame rate based on visual input. To this end, he develops key technology to invert the image formation models of computer graphics based on data-parallel optimization and state-of-the-art deep learning techniques.
Website: https://web.stanford.edu/~zollhoef/
Prof. Dr. Christian Theobalt is a Professor of Computer Science and the head of the research group "Graphics, Vision, & Video" at the Max-Planck-Institute (MPI) 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 Saarland University and 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, marker-less motion and performance capture, virtual and augmented reality, computer animation, appearance and reflectance modelling, intrinsic video and inverse rendering, machine learning for graphics and vision, new sensors for 3D acquisition, advanced video processing, 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, and the Karl Heinz Beckurts Award in 2017. He received two ERC grants, an ERC Starting Grant in 2013 and an ERC Consolidator Grant in 2017. In 2015, he was elected as one of the top 40 innovation leaders under 40 in Germany by the business magazine Capital. Christian Theobalt is also a co-founder of an award-winning spin-off company from his group - www.thecaptury.com - that is commercializing one of the most advanced solutions for marker-less motion and performance capture.
Website: http://gvv.mpi-inf.mpg.de/
Prof. Dr. Matthias Niessner is heading the Visual Computing Lab at Technical University of Munich (TUM). He obtained his PhD from the University of Erlangen-Nuremberg in 2013, and was a Visiting Assistant Professor at Stanford University from 2013 to 2017. Since 2017 he is Professor at TUM focusing on cutting-edge research at the intersection of computer vision, graphics, and machine learning. He is particularly interested in novel techniques for 3D reconstruction, semantic 3D scene understanding, and video editing. In addition to his academic career, Prof. Nießner is a co-founder and director of Synthesia Inc., a startup empowering storytellers with AI. Prof. Nießner is a TUM-IAS Rudolph Moessbauer Fellow, and he has received the Google Faculty Award for Machine Perception (2017), the Nvidia Professor Partnership Award (2018), as well as the ERC Starting Grant 2018.
Website: http://niessnerlab.org