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Visual Computing and Artificial Intelligence Department

Advanced Topics in Neural Rendering and Reconstruction

Lecture – Winter Semester 2023/2024

Mohamed Elgharib, Vladislav Golyanik, Thomas Leimkühler, Marc Habermann, Christian Theobalt

Organization  |  Content  |  Resources

Clockwise direction: Habermann et al. DeepCap 2020, Rudnev et al. NeRF-OSR 2022, Pan et al. DragGAN 2023, Rudnev et al. EventNeRF 2023

Course Description

Neural rendering and reconstruction is the cornerstone of digitizing our world, with several applications in VR/AR, movie and media production, robotics, and many more. The digitization pipeline usually consists of three main stages; data capture, 3D model building, and finally, reconstruction and rendering/synthesis. This course will cover advanced topics in this digitization pipeline, with a focus on data-driven approaches using neural-based formulations. We will cover 3D scene representations, including explicit approaches as well as the more recent learnable implicit-based approaches. We will discuss how to build 3D morphable models for important objects such as the human face and body. We will also cover approaches for both 2D and 3D neural rendering. While the vast majority of the topics will focus on using data captured by RGB cameras, we will also discuss other means of capturing data using advanced sensors such as IMUs and event cameras. Finally, we will discuss quantum visual computing and the impact it can bring to the field.


If have questions about this lecture, please contact us at elgharib@mpi-inf.mpg.de


Registeration will be possible through the University of Saarland. More information coming soon.


The course is more tailored towards the students of Visual Computing (M.Sc.), Computer Science (M.Sc.) and Data Science and Artificial Intelligence (M.Sc.).

It is preferred, but not necessarily required, that students have already studied IPCV and Computer Graphics 1, or something equivalent.

Schedule and other details:

Format: 1 lecture per week. Only in person attendance.
Registeration: Registeration is possible through the CMS-System.
Time: Wednesdays from 14:00-16:00
Location: Lecture hall 003 in E1 3
Credit Points: 3 CP
Lecture Slides: Slides are accessible through this link.