Advanced Topics in Neural Rendering and Reconstruction
Lecture – Winter Semester 2024/2025
Thomas Leimkühler, Rishabh Dabral, Marc Habermann, Vladislav Golyanik, Christian Theobalt
Organization | Content | Resources
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| Top left: Habermann et al., DeepCap 2020. Top right: Laine et al., Modular Primitives for High-Performance Differentiable Rendering, 2020. Bottom left: Rathi et al., 3D-QAE: Fully Quantum Auto-Encoding of 3D Point Clouds, 2023. Bottom right: Yang et al., Diffusion Models, 2024 |
Course Description
Neural rendering and reconstruction form the foundation of digitizing the physical world, with applications in virtual/augmented reality (VR/AR), film production, robotics, and beyond. This course explores advanced topics in this space, emphasizing data-driven approaches using neural models. After reviewing the basics of computer graphics and machine learning, we will delve into 3D scene representation and reconstruction using differentiable rendering, generative models, morphable models, human reconstruction and synthesis, and quantum visual computing.Organization
If you have questions about this lecture, please contact us via thomas.leimkuehler@mpi-inf.mpg.de.
Prerequisites
The course is tailored towards 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 Image Processing and Computer Vision and Computer Graphics 1, or something equivalent.
Schedule and other details
| Registration: | Please register in the CMS. Please do not forget to register for the exam in the HISPOS system. |
| Format: | 1 lecture per week, in-person attendance |
| Time: | Wednesdays, 14:15-15:45 |
| Location: | E1.3, lecture hall 003 |
| Credit Points: | 3 CP |
| Exam: | Final exam: 24.02., 14:00-16:00. Re-exam: 17.03., 14:00-16:00. Both exams will be held in E1.3, lecture hall 003. |
| Lecture Slides: | Available for download in the CMS for registered students |